A Comprehensive Survey of Multiagent Reinforcement Learning
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many tasks arising in these domains makes them difficult to solve with preprogrammed agent behaviors. The agents must, instead, d...
Saved in:
| Published in | IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews Vol. 38; no. 2; pp. 156 - 172 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
IEEE
01.03.2008
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many tasks arising in these domains makes them difficult to solve with preprogrammed agent behaviors. The agents must, instead, discover a solution on their own, using learning. A significant part of the research on multiagent learning concerns reinforcement learning techniques. This paper provides a comprehensive survey of multiagent reinforcement learning (MARL). A central issue in the field is the formal statement of the multiagent learning goal. Different viewpoints on this issue have led to the proposal of many different goals, among which two focal points can be distinguished: stability of the agents' learning dynamics, and adaptation to the changing behavior of the other agents. The MARL algorithms described in the literature aim---either explicitly or implicitly---at one of these two goals or at a combination of both, in a fully cooperative, fully competitive, or more general setting. A representative selection of these algorithms is discussed in detail in this paper, together with the specific issues that arise in each category. Additionally, the benefits and challenges of MARL are described along with some of the problem domains where the MARL techniques have been applied. Finally, an outlook for the field is provided. |
|---|---|
| AbstractList | Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many tasks arising in these domains makes them difficult to solve with preprogrammed agent behaviors. The agents must, instead, discover a solution on their own, using learning. A significant part of the research on multiagent learning concerns reinforcement learning techniques. This paper provides a comprehensive survey of multiagent reinforcement learning (MARL). A central issue in the field is the formal statement of the multiagent learning goal. Different viewpoints on this issue have led to the proposal of many different goals, among which two focal points can be distinguished: stability of the agents' learning dynamics, and adaptation to the changing behavior of the other agents. The MARL algorithms described in the literature aim---either explicitly or implicitly---at one of these two goals or at a combination of both, in a fully cooperative, fully competitive, or more general setting. A representative selection of these algorithms is discussed in detail in this paper, together with the specific issues that arise in each category. Additionally, the benefits and challenges of MARL are described along with some of the problem domains where the MARL techniques have been applied. Finally, an outlook for the field is provided. |
| Author | De Schutter, B. Babuska, R. Busoniu, L. |
| Author_xml | – sequence: 1 givenname: L. surname: Busoniu fullname: Busoniu, L. organization: Delft Univ. of Technol., Delft – sequence: 2 givenname: R. surname: Babuska fullname: Babuska, R. organization: Delft Univ. of Technol., Delft – sequence: 3 givenname: B. surname: De Schutter fullname: De Schutter, B. |
| BookMark | eNp9kD1PwzAQQC1UJFrgByCWbEwpdmLHsZiqiC-pFRIts-W452KU2MVOKvXf0xLEwMB0d9J7N7wJGjnvAKErgqeEYHG7Wi6qapphzKeC5IKIEzQmjJVpRmk2OuxY0LQQnJ-hSYwfGBNKRT5Gd7Ok8u02wDu4aHeQLPuwg33iTbLom86qDbgueQXrjA8a2uM1BxWcdZsLdGpUE-HyZ56jt4f7VfWUzl8en6vZPNV5RrtUG73OwAiRa5xrzrQqYF2KrMDUKEVYjTWnwtRGKGL4moMShJC60MBqJgqVn6Ob4e82-M8eYidbGzU0jXLg-yhLzjDDZSYOJB9IHXyMAYzUtlOd9a4LyjaSYHmsJb9ryWMtOdQ6mOSPuQ22VWH_r3M9OBYAfnlKKeOM5187i3ir |
| CODEN | ITCRFH |
| CitedBy_id | crossref_primary_10_3390_e20040236 crossref_primary_10_1007_s00521_024_10598_0 crossref_primary_10_1016_j_swevo_2022_101085 crossref_primary_10_1109_TWC_2019_2933417 crossref_primary_10_1063_5_0141824 crossref_primary_10_1016_j_artint_2024_104094 crossref_primary_10_1371_journal_pone_0145526 crossref_primary_10_2478_ttj_2020_0024 crossref_primary_10_1109_ACCESS_2019_2931884 crossref_primary_10_1016_j_sysconle_2023_105563 crossref_primary_10_1088_1742_6596_1235_1_012022 crossref_primary_10_1109_TCCN_2018_2881135 crossref_primary_10_1016_j_ejor_2022_12_022 crossref_primary_10_1007_s10458_024_09662_9 crossref_primary_10_1016_j_aej_2024_09_032 crossref_primary_10_1016_j_cor_2016_12_007 crossref_primary_10_1109_TCYB_2018_2856089 crossref_primary_10_1093_comjnl_bxae008 crossref_primary_10_1145_3706110 crossref_primary_10_1109_TCCN_2019_2933420 crossref_primary_10_1016_j_asoc_2024_112203 crossref_primary_10_1016_j_robot_2010_09_006 crossref_primary_10_1007_s12530_024_09622_4 crossref_primary_10_1109_JIOT_2021_3131719 crossref_primary_10_1109_TSP_2016_2548987 crossref_primary_10_1109_OJCOMS_2024_3480987 crossref_primary_10_1016_j_automatica_2024_111762 crossref_primary_10_1002_rnc_3413 crossref_primary_10_1007_s10458_019_09411_3 crossref_primary_10_1111_exsy_13315 crossref_primary_10_1016_j_comcom_2023_11_006 crossref_primary_10_1109_LRA_2023_3261750 crossref_primary_10_1016_j_artint_2010_09_008 crossref_primary_10_1007_s11042_024_19054_6 crossref_primary_10_1016_j_jai_2024_02_003 crossref_primary_10_1109_TCYB_2014_2341582 crossref_primary_10_4213_tvp5231 crossref_primary_10_1109_OJCOMS_2024_3509440 crossref_primary_10_1109_TSMC_2015_2504350 crossref_primary_10_1016_j_ins_2023_03_074 crossref_primary_10_1109_JSYST_2012_2208809 crossref_primary_10_1109_TSMCC_2010_2057424 crossref_primary_10_1109_ACCESS_2024_3482711 crossref_primary_10_1137_22M1505475 crossref_primary_10_1109_ACCESS_2022_3148473 crossref_primary_10_1016_j_ins_2012_02_043 crossref_primary_10_1109_TAC_2017_2734840 crossref_primary_10_1109_TWC_2022_3178767 crossref_primary_10_1088_1748_3190_ac9fb5 crossref_primary_10_1109_TCYB_2016_2543238 crossref_primary_10_1007_s12555_012_0119_9 crossref_primary_10_1016_j_patcog_2023_109917 crossref_primary_10_1016_j_eswa_2021_114896 crossref_primary_10_1137_140963765 crossref_primary_10_1016_j_jnca_2012_04_021 crossref_primary_10_1109_TITS_2023_3343452 crossref_primary_10_1109_TNNLS_2020_3025711 crossref_primary_10_1145_3606926 crossref_primary_10_1016_j_neucom_2016_01_031 crossref_primary_10_1109_TNNLS_2023_3280161 crossref_primary_10_1002_spe_2778 crossref_primary_10_1016_j_engappai_2023_106693 crossref_primary_10_1109_TNNLS_2013_2283574 crossref_primary_10_1049_iet_its_2020_0443 crossref_primary_10_1007_s10458_016_9347_3 crossref_primary_10_1109_ACCESS_2021_3094623 crossref_primary_10_1287_opre_2021_2226 crossref_primary_10_1145_3579476 crossref_primary_10_1109_TCST_2014_2312392 crossref_primary_10_1016_j_adhoc_2019_101880 crossref_primary_10_9746_sicetr_51_352 crossref_primary_10_1109_TCYB_2019_2932203 crossref_primary_10_1007_s10994_022_06286_6 crossref_primary_10_1145_3320496_3320500 crossref_primary_10_1016_j_asoc_2014_08_071 crossref_primary_10_1016_j_cor_2014_01_008 crossref_primary_10_1016_j_automatica_2012_05_074 crossref_primary_10_1109_TCYB_2020_2985043 crossref_primary_10_1145_3168446 crossref_primary_10_1016_j_trc_2024_104528 crossref_primary_10_1007_s00158_022_03210_3 crossref_primary_10_1007_s10458_019_09433_x crossref_primary_10_3390_s21154979 crossref_primary_10_1109_LCSYS_2020_3021050 crossref_primary_10_1109_COMST_2021_3086014 crossref_primary_10_2514_1_I010973 crossref_primary_10_1109_TSMCC_2010_2044174 crossref_primary_10_1016_j_apenergy_2022_118825 crossref_primary_10_1109_TITS_2024_3410023 crossref_primary_10_1061_JBENF2_BEENG_6159 crossref_primary_10_1007_s10846_010_9396_9 crossref_primary_10_3390_math10244673 crossref_primary_10_1109_TSMC_2014_2358639 crossref_primary_10_1016_j_comcom_2019_09_002 crossref_primary_10_1007_s10846_020_01237_6 crossref_primary_10_1016_j_future_2016_06_039 crossref_primary_10_1016_j_ress_2022_109013 crossref_primary_10_3390_app142110079 crossref_primary_10_1007_s11768_020_00007_x crossref_primary_10_3233_IA_210081 crossref_primary_10_3390_s20164546 crossref_primary_10_1016_j_advengsoft_2023_103487 crossref_primary_10_1587_transinf_E94_D_255 crossref_primary_10_3390_app9061089 crossref_primary_10_1016_j_neucom_2017_07_027 crossref_primary_10_1016_j_ins_2012_12_021 crossref_primary_10_1007_s11768_015_3203_x crossref_primary_10_1109_TNNLS_2015_2403394 crossref_primary_10_1016_j_arcontrol_2020_03_001 crossref_primary_10_1016_j_arcontrol_2022_03_003 crossref_primary_10_1016_j_jocs_2020_101280 crossref_primary_10_1109_ACCESS_2024_3409051 crossref_primary_10_1155_2013_437926 crossref_primary_10_1109_LCSYS_2023_3329072 crossref_primary_10_1016_j_eswa_2025_126565 crossref_primary_10_1109_TAES_2021_3130832 crossref_primary_10_1016_j_energy_2018_04_042 crossref_primary_10_1109_TCCN_2020_3027695 crossref_primary_10_1007_s10458_024_09666_5 crossref_primary_10_1109_TCSS_2021_3100291 crossref_primary_10_1109_TCST_2020_3016077 crossref_primary_10_1016_j_oceaneng_2022_112182 crossref_primary_10_1088_1742_6596_1651_1_012017 crossref_primary_10_1109_TWC_2022_3233853 crossref_primary_10_1007_s11276_014_0844_5 crossref_primary_10_1109_TITS_2021_3096226 crossref_primary_10_1016_j_arcontrol_2018_09_005 crossref_primary_10_1186_s13638_017_1018_9 crossref_primary_10_1007_s10458_016_9352_6 crossref_primary_10_1145_3579443 crossref_primary_10_1016_j_procir_2019_02_099 crossref_primary_10_1049_cth2_12473 crossref_primary_10_1016_j_asoc_2014_06_021 crossref_primary_10_1016_j_automatica_2021_109685 crossref_primary_10_1007_s11042_023_16376_9 crossref_primary_10_1016_j_phycom_2022_101845 crossref_primary_10_1016_j_amc_2013_06_086 crossref_primary_10_2200_S01091ED1V01Y202104AIM049 crossref_primary_10_3390_electronics13245040 crossref_primary_10_1016_j_asoc_2020_106700 crossref_primary_10_1007_s00521_021_05918_7 crossref_primary_10_3390_smartcities5010019 crossref_primary_10_3390_e24040470 crossref_primary_10_1007_s10462_015_9438_6 crossref_primary_10_1109_TVT_2022_3196046 crossref_primary_10_1109_JIOT_2023_3289888 crossref_primary_10_1109_TG_2022_3232390 crossref_primary_10_1016_j_artint_2016_03_005 crossref_primary_10_1016_j_apenergy_2022_118636 crossref_primary_10_1109_TITS_2013_2255286 crossref_primary_10_1145_3708320 crossref_primary_10_1109_TSMCC_2012_2218596 crossref_primary_10_3390_app13031936 crossref_primary_10_1016_j_neucom_2021_10_093 crossref_primary_10_1007_s00521_017_3223_1 crossref_primary_10_1016_j_robot_2017_03_003 crossref_primary_10_1137_S0040585X97T989386 crossref_primary_10_1016_j_oceaneng_2023_116403 crossref_primary_10_1109_TAC_2020_2978037 crossref_primary_10_1371_journal_pone_0234434 crossref_primary_10_1109_JIOT_2020_3004339 crossref_primary_10_1109_TAES_2023_3270858 crossref_primary_10_1109_TNNLS_2022_3202097 crossref_primary_10_1007_s00521_023_09096_6 crossref_primary_10_1016_j_scico_2024_103176 crossref_primary_10_1016_j_artmed_2021_102137 crossref_primary_10_1109_COMST_2019_2916177 crossref_primary_10_1016_j_eswa_2010_12_152 crossref_primary_10_1109_TKDE_2020_3014246 crossref_primary_10_1109_LCOMM_2021_3088841 crossref_primary_10_1145_3665927 crossref_primary_10_3390_electronics12214496 crossref_primary_10_1109_TASE_2024_3398712 crossref_primary_10_1007_s12239_022_0056_4 crossref_primary_10_3390_fi14010017 crossref_primary_10_1109_TIE_2020_2988189 crossref_primary_10_1016_j_enconman_2016_05_039 crossref_primary_10_1631_FITEE_2100594 crossref_primary_10_1049_cth2_12677 crossref_primary_10_1109_TCIAIG_2012_2212279 crossref_primary_10_1155_2014_932485 crossref_primary_10_1049_iet_cta_2018_0029 crossref_primary_10_1109_TNSE_2021_3121690 crossref_primary_10_1527_tjsai_36_5_E_K62 crossref_primary_10_1007_s10846_013_9980_x crossref_primary_10_3328_TL_2010_02_02_89_110 crossref_primary_10_1016_j_sbspro_2014_01_146 crossref_primary_10_1007_s10462_015_9447_5 crossref_primary_10_1109_ACCESS_2019_2893871 crossref_primary_10_1109_ACCESS_2018_2853263 crossref_primary_10_1016_j_future_2020_11_017 crossref_primary_10_1016_j_neucom_2024_128811 crossref_primary_10_1002_cpe_2947 crossref_primary_10_1007_s10845_023_02309_8 crossref_primary_10_1016_j_dental_2020_03_021 crossref_primary_10_1016_j_epsr_2022_108806 crossref_primary_10_1109_JIOT_2019_2955035 crossref_primary_10_1109_TPWRS_2014_2357079 crossref_primary_10_1016_j_eswa_2023_120495 crossref_primary_10_1109_TETCI_2021_3082204 crossref_primary_10_1177_09544054221080031 crossref_primary_10_1109_LRA_2017_2734247 crossref_primary_10_1016_j_artint_2020_103438 crossref_primary_10_1016_j_chaos_2023_113332 crossref_primary_10_3390_electronics12122614 crossref_primary_10_1109_LRA_2025_3550743 crossref_primary_10_1177_00375497241237831 crossref_primary_10_1109_MCOM_001_1900530 crossref_primary_10_1007_s11432_023_3955_x crossref_primary_10_1016_j_eswa_2023_120186 crossref_primary_10_63053_ijset_60 crossref_primary_10_1080_0022250X_2018_1517761 crossref_primary_10_1016_j_parco_2018_03_006 crossref_primary_10_1109_TTE_2023_3236324 crossref_primary_10_1287_moor_2022_1268 crossref_primary_10_1007_s11403_017_0204_5 crossref_primary_10_1016_j_neucom_2022_01_025 crossref_primary_10_1109_TNNLS_2020_2996209 crossref_primary_10_1109_JIOT_2021_3078514 crossref_primary_10_1109_SURV_2013_030713_00113 crossref_primary_10_3390_math9233081 crossref_primary_10_1007_s10994_021_06033_3 crossref_primary_10_1186_s12859_019_3126_5 crossref_primary_10_1109_TMC_2021_3077636 crossref_primary_10_1109_TSUSC_2020_3025139 crossref_primary_10_1080_17517575_2019_1585578 crossref_primary_10_1145_3058592 crossref_primary_10_1109_TVT_2022_3160446 crossref_primary_10_1007_s13235_023_00490_2 crossref_primary_10_1016_j_eswa_2010_11_024 crossref_primary_10_1109_ACCESS_2018_2878853 crossref_primary_10_1007_s11107_020_00906_8 crossref_primary_10_1016_j_arcontrol_2012_03_004 crossref_primary_10_1103_PhysRevE_99_043305 crossref_primary_10_4018_IJIDE_2019070104 crossref_primary_10_1109_TCYB_2020_3025491 crossref_primary_10_1007_s10614_022_10351_6 crossref_primary_10_1016_j_watres_2024_121145 crossref_primary_10_1021_acs_iecr_2c00335 crossref_primary_10_1016_j_aej_2024_12_110 crossref_primary_10_1007_s00521_021_06117_0 crossref_primary_10_3390_a15070227 crossref_primary_10_1109_MSP_2017_2743240 crossref_primary_10_1109_TIM_2020_2985553 crossref_primary_10_1109_TSMCC_2010_2099654 crossref_primary_10_1109_TVT_2017_2702388 crossref_primary_10_1145_3345319 crossref_primary_10_1631_FITEE_2200055 crossref_primary_10_1109_TAC_2016_2585302 crossref_primary_10_3389_fnbot_2022_932671 crossref_primary_10_1145_3709371 crossref_primary_10_1016_j_geits_2024_100157 crossref_primary_10_1016_j_eswa_2021_116323 crossref_primary_10_1109_ACCESS_2021_3056903 crossref_primary_10_3390_info14110623 crossref_primary_10_1017_S0269888920000119 crossref_primary_10_1016_j_ifacol_2019_09_144 crossref_primary_10_1109_TAC_2022_3159453 crossref_primary_10_1109_ACCESS_2023_3266644 crossref_primary_10_1021_ie4031743 crossref_primary_10_1109_LRA_2022_3184795 crossref_primary_10_1007_s10458_011_9181_6 crossref_primary_10_1109_TSG_2015_2453884 crossref_primary_10_1109_TCYB_2020_2963849 crossref_primary_10_1016_j_aeue_2013_04_002 crossref_primary_10_1007_s10846_021_01477_0 crossref_primary_10_1016_j_camwa_2012_01_079 crossref_primary_10_1109_TNSE_2022_3201121 crossref_primary_10_1109_TIA_2022_3218274 crossref_primary_10_1080_18756891_2012_718154 crossref_primary_10_3233_AIC_180766 crossref_primary_10_1527_tjsai_36_5_AG21_H crossref_primary_10_1016_j_arcontrol_2022_07_004 crossref_primary_10_1109_ACCESS_2019_2915541 crossref_primary_10_3390_app8101911 crossref_primary_10_1109_TRO_2016_2597322 crossref_primary_10_1007_s10462_018_9639_x crossref_primary_10_1177_1059712316679239 crossref_primary_10_1016_j_jksuci_2024_102254 crossref_primary_10_1002_ett_2810 crossref_primary_10_3390_electronics12081803 crossref_primary_10_1016_j_physd_2024_134096 crossref_primary_10_1109_TNET_2023_3267168 crossref_primary_10_1109_TSMC_2018_2853126 crossref_primary_10_1109_TSIPN_2017_2787910 crossref_primary_10_1109_TSMC_2014_2373336 crossref_primary_10_1007_s10479_012_1098_1 crossref_primary_10_1109_ACCESS_2021_3087410 crossref_primary_10_1155_2020_9207324 crossref_primary_10_1109_TCAD_2020_2971529 crossref_primary_10_1109_JAS_2022_105809 crossref_primary_10_1115_1_4062883 crossref_primary_10_1016_j_robot_2019_103293 crossref_primary_10_1007_s10462_021_09996_w crossref_primary_10_1016_j_adhoc_2020_102147 crossref_primary_10_1016_j_cogr_2023_07_004 crossref_primary_10_1007_s41870_023_01264_0 crossref_primary_10_1103_PhysRevE_111_014106 crossref_primary_10_1109_OJCSYS_2023_3277760 crossref_primary_10_3390_robotics8040082 crossref_primary_10_1016_j_neucom_2016_08_108 crossref_primary_10_1049_iet_gtd_2009_0168 crossref_primary_10_1155_2015_597956 crossref_primary_10_1109_MSP_2020_2976000 crossref_primary_10_1016_j_apenergy_2024_123870 crossref_primary_10_1007_s11276_013_0572_2 crossref_primary_10_1007_s10458_023_09603_y crossref_primary_10_1145_3450626_3459761 crossref_primary_10_1177_1548512910382002 crossref_primary_10_1016_j_jtbi_2024_112032 crossref_primary_10_1109_ACCESS_2020_2966226 crossref_primary_10_1016_j_asoc_2009_09_006 crossref_primary_10_1049_iet_cta_2018_6266 crossref_primary_10_1007_s11151_019_09689_3 crossref_primary_10_3389_fphy_2020_00200 crossref_primary_10_3390_e23091133 crossref_primary_10_1007_s11721_013_0078_7 crossref_primary_10_2139_ssrn_3960738 crossref_primary_10_1109_TWC_2024_3378293 crossref_primary_10_1007_s12046_024_02574_0 crossref_primary_10_1109_JIOT_2017_2761353 crossref_primary_10_1080_08839514_2014_862774 crossref_primary_10_3390_drones8030071 crossref_primary_10_1080_09540091_2014_885282 crossref_primary_10_1109_TNNLS_2021_3056418 crossref_primary_10_1016_j_automatica_2024_111803 crossref_primary_10_25299_itjrd_2023_13474 crossref_primary_10_1109_TSC_2021_3124419 crossref_primary_10_1142_S1752890922410033 crossref_primary_10_1109_TWC_2023_3240425 crossref_primary_10_1109_TVT_2019_2953809 crossref_primary_10_1016_j_asoc_2014_01_004 crossref_primary_10_1111_coin_12035 crossref_primary_10_3156_jsoft_24_1002 crossref_primary_10_1016_j_asej_2024_102688 crossref_primary_10_1109_MNET_011_1900628 crossref_primary_10_1109_TCYB_2020_2979803 crossref_primary_10_1016_j_neucom_2021_06_049 crossref_primary_10_1007_s13218_014_0312_5 crossref_primary_10_1080_09540091_2014_885294 crossref_primary_10_1109_TSMC_2024_3414832 crossref_primary_10_1115_1_4045044 crossref_primary_10_1002_acs_2862 crossref_primary_10_1016_j_imavis_2014_08_009 crossref_primary_10_1007_s10796_022_10333_x crossref_primary_10_3389_frsgr_2024_1371153 crossref_primary_10_1109_TSMCC_2011_2162401 crossref_primary_10_1109_TWC_2016_2616400 crossref_primary_10_1016_j_ins_2024_120996 crossref_primary_10_1016_j_mlwa_2022_100341 crossref_primary_10_1007_s12555_015_0465_5 crossref_primary_10_1109_TITS_2018_2849824 crossref_primary_10_1109_TCYB_2014_2332042 crossref_primary_10_3390_su152416741 crossref_primary_10_1007_s11276_024_03753_x crossref_primary_10_1038_s42256_024_00879_7 crossref_primary_10_1177_0278364918812981 crossref_primary_10_1177_1059712312449547 crossref_primary_10_1109_TCSI_2023_3250516 crossref_primary_10_1109_LCOMM_2019_2896929 crossref_primary_10_1109_TITS_2019_2893683 crossref_primary_10_2139_ssrn_3912066 crossref_primary_10_1007_s10458_014_9257_1 crossref_primary_10_1016_j_artint_2019_103216 crossref_primary_10_1115_1_4052800 crossref_primary_10_3390_electronics11091456 crossref_primary_10_1109_LRA_2022_3214446 crossref_primary_10_1109_TNSE_2024_3375374 crossref_primary_10_1109_TVT_2024_3409687 crossref_primary_10_2139_ssrn_4021959 crossref_primary_10_1109_TII_2019_2902563 crossref_primary_10_2478_v10177_011_0031_x crossref_primary_10_1109_TBC_2021_3068872 crossref_primary_10_1109_TMM_2023_3270635 crossref_primary_10_1109_TSG_2019_2952331 crossref_primary_10_1017_S089006042100024X crossref_primary_10_1109_TVT_2022_3189019 crossref_primary_10_3390_s21092970 crossref_primary_10_3390_robotics7040066 crossref_primary_10_1145_3603703 crossref_primary_10_1007_s12065_022_00766_3 crossref_primary_10_1016_j_neucom_2021_07_014 crossref_primary_10_1109_TNSE_2023_3306202 crossref_primary_10_1109_TSMCC_2011_2161577 crossref_primary_10_1109_TCAD_2022_3222670 crossref_primary_10_1609_aimag_v33i3_2422 crossref_primary_10_1155_2010_876216 crossref_primary_10_1186_s40309_024_00238_0 crossref_primary_10_1016_j_compchemeng_2021_107382 crossref_primary_10_1162_tacl_a_00037 crossref_primary_10_1038_s41467_022_34473_5 crossref_primary_10_1016_j_paerosci_2024_101005 crossref_primary_10_1609_aimag_v33i3_2426 crossref_primary_10_1016_j_cherd_2024_12_028 crossref_primary_10_1109_JIOT_2022_3188833 crossref_primary_10_1109_TCYB_2017_2781130 crossref_primary_10_1109_TMC_2021_3120050 crossref_primary_10_1680_jtran_17_00085 crossref_primary_10_1002_asjc_614 crossref_primary_10_1109_ACCESS_2020_3034141 crossref_primary_10_1007_s00779_015_0888_2 crossref_primary_10_1016_j_jss_2013_12_029 crossref_primary_10_1587_transfun_E102_A_708 crossref_primary_10_1016_j_amc_2021_126370 crossref_primary_10_1109_JSAC_2013_131115 crossref_primary_10_1631_FITEE_1900661 crossref_primary_10_1038_s41578_022_00513_1 crossref_primary_10_1109_JSAIT_2022_3231459 crossref_primary_10_1016_j_neucom_2024_128015 crossref_primary_10_1109_ACCESS_2023_3345448 crossref_primary_10_1007_s00500_021_05715_3 crossref_primary_10_1007_s10462_021_10061_9 crossref_primary_10_1109_ACCESS_2019_2946659 crossref_primary_10_3233_IA_190037 crossref_primary_10_1109_JSAC_2023_3345399 crossref_primary_10_1109_ACCESS_2019_2943146 crossref_primary_10_1016_j_asoc_2015_09_017 crossref_primary_10_1109_TITS_2016_2577037 crossref_primary_10_1016_j_automatica_2016_05_017 crossref_primary_10_1109_JIOT_2020_3009540 crossref_primary_10_1155_2018_7172614 crossref_primary_10_9746_sicetr_49_39 crossref_primary_10_1109_LCOMM_2025_3535898 crossref_primary_10_3182_20100712_3_FR_2020_00080 crossref_primary_10_1109_TSG_2014_2363844 crossref_primary_10_1109_ACCESS_2020_3027355 crossref_primary_10_3389_frobt_2024_1336612 crossref_primary_10_1109_ACCESS_2023_3340867 crossref_primary_10_1115_1_4067718 crossref_primary_10_1007_s11590_023_02009_5 crossref_primary_10_1126_scirobotics_aat0430 crossref_primary_10_1109_TIE_2015_2420792 crossref_primary_10_1007_s10462_022_10299_x crossref_primary_10_3390_app13042750 crossref_primary_10_1016_j_apenergy_2020_116382 crossref_primary_10_3390_math10163017 crossref_primary_10_1007_s10458_021_09541_7 crossref_primary_10_1109_TCYB_2013_2253094 crossref_primary_10_1109_ACCESS_2019_2916155 crossref_primary_10_2478_jaiscr_2020_0013 crossref_primary_10_1007_s10458_023_09633_6 crossref_primary_10_1049_esi2_12030 crossref_primary_10_1007_s11390_019_1933_9 crossref_primary_10_1016_j_comnet_2022_109462 crossref_primary_10_1016_j_neucom_2014_05_070 crossref_primary_10_1109_TCC_2021_3117956 crossref_primary_10_3389_frai_2022_805823 crossref_primary_10_32628_CSEIT2390147 crossref_primary_10_1016_j_trc_2017_11_011 crossref_primary_10_3390_app11188291 crossref_primary_10_1109_LWC_2019_2904486 crossref_primary_10_1142_S0219691316500533 crossref_primary_10_1016_j_automatica_2014_10_047 crossref_primary_10_1016_j_chaos_2023_113809 crossref_primary_10_1109_TCYB_2014_2387277 crossref_primary_10_1002_ett_3692 crossref_primary_10_1016_j_array_2022_100142 crossref_primary_10_1016_j_engappai_2013_09_001 crossref_primary_10_1109_ACCESS_2020_3043806 crossref_primary_10_1360_SSI_2021_0179 crossref_primary_10_1109_TWC_2023_3279268 crossref_primary_10_1002_rnc_3719 crossref_primary_10_1109_TII_2017_2753408 crossref_primary_10_1016_j_ress_2023_109687 crossref_primary_10_1360_SST_2021_0376 crossref_primary_10_1007_s13235_022_00449_9 crossref_primary_10_1007_s10458_019_09421_1 crossref_primary_10_1016_j_neucom_2024_128068 crossref_primary_10_1109_LRA_2020_3013920 crossref_primary_10_1016_j_neunet_2025_107253 crossref_primary_10_1108_IJIUS_06_2018_0016 crossref_primary_10_2139_ssrn_4102541 crossref_primary_10_1109_TRO_2024_3431829 crossref_primary_10_1016_j_artint_2018_01_002 crossref_primary_10_1080_00051144_2019_1674512 crossref_primary_10_1016_j_ifacol_2019_12_156 crossref_primary_10_1145_3476576_3476725 crossref_primary_10_1093_nsr_nwac256 crossref_primary_10_1016_j_ejcon_2023_100853 crossref_primary_10_1541_ieejeiss_145_299 crossref_primary_10_1109_COMST_2021_3102580 crossref_primary_10_1016_j_engappai_2019_06_019 crossref_primary_10_1016_j_knosys_2015_10_022 crossref_primary_10_1109_TMC_2024_3409050 crossref_primary_10_20965_jaciii_2013_p0272 crossref_primary_10_1109_TNNLS_2023_3302131 crossref_primary_10_1109_ACCESS_2021_3110255 crossref_primary_10_1109_LCOMM_2022_3144451 crossref_primary_10_1016_j_ic_2022_104886 crossref_primary_10_1115_1_4065343 crossref_primary_10_7717_peerj_cs_575 crossref_primary_10_1109_JSAC_2019_2904366 crossref_primary_10_1016_j_neucom_2017_04_074 crossref_primary_10_1145_3625544 crossref_primary_10_1016_j_trb_2023_02_015 crossref_primary_10_1007_s10489_022_04105_y crossref_primary_10_1016_j_asoc_2021_108023 crossref_primary_10_1109_JAS_2021_1003814 crossref_primary_10_1016_j_enconman_2015_06_030 crossref_primary_10_1016_j_compbiomed_2024_108257 crossref_primary_10_1109_OJCOMS_2023_3265425 crossref_primary_10_1109_TCNS_2021_3074218 crossref_primary_10_1109_TMC_2022_3190449 crossref_primary_10_1109_TITS_2014_2308975 crossref_primary_10_1007_s00521_016_2354_0 crossref_primary_10_1007_s10458_022_09582_6 crossref_primary_10_1109_TCYB_2019_2958912 crossref_primary_10_1016_j_adhoc_2014_09_012 crossref_primary_10_3390_en14144323 crossref_primary_10_1093_bioinformatics_bty323 crossref_primary_10_1088_1742_6596_1995_1_012023 crossref_primary_10_1109_TCYB_2019_2921057 crossref_primary_10_1186_1678_4804_20_15 crossref_primary_10_1007_s13042_024_02170_y crossref_primary_10_1007_s10845_013_0864_5 crossref_primary_10_1016_j_engappai_2015_01_017 crossref_primary_10_1017_S0269888912000057 crossref_primary_10_1007_s11432_023_3853_y crossref_primary_10_1016_j_energy_2024_132997 crossref_primary_10_1016_j_cie_2016_02_022 crossref_primary_10_1016_j_artint_2015_02_004 crossref_primary_10_1016_j_jpdc_2021_05_003 crossref_primary_10_1016_j_comcom_2023_08_012 crossref_primary_10_1016_j_neucom_2013_07_020 crossref_primary_10_1109_TGCN_2021_3056235 crossref_primary_10_1109_JSAC_2021_3118346 crossref_primary_10_1109_ACCESS_2023_3279401 crossref_primary_10_1016_j_cap_2024_03_003 crossref_primary_10_1007_s11227_015_1420_1 crossref_primary_10_1002_cpe_1759 crossref_primary_10_1016_j_ins_2022_10_022 crossref_primary_10_1057_jors_2013_19 crossref_primary_10_1109_JSSC_2019_2935533 crossref_primary_10_1109_ACCESS_2023_3268754 crossref_primary_10_23919_JSEE_2024_000062 crossref_primary_10_3390_s24020707 crossref_primary_10_3390_act10100268 crossref_primary_10_1016_j_neucom_2020_01_079 crossref_primary_10_1002_cpe_2870 crossref_primary_10_1016_j_inffus_2025_103107 crossref_primary_10_1145_3701621 crossref_primary_10_1016_j_apm_2012_04_019 crossref_primary_10_1016_j_ifacol_2022_07_618 crossref_primary_10_1541_ieejeiss_132_1819 crossref_primary_10_1016_j_trc_2019_04_012 crossref_primary_10_1007_s11227_021_04013_x crossref_primary_10_1016_j_oceaneng_2024_120244 crossref_primary_10_1007_s10458_020_09442_1 crossref_primary_10_1109_JPROC_2021_3072740 crossref_primary_10_1007_s10115_018_1234_6 crossref_primary_10_1007_s43508_023_00074_1 crossref_primary_10_1109_TCDS_2018_2840971 crossref_primary_10_1016_j_adapen_2023_100151 crossref_primary_10_1109_ACCESS_2021_3086002 crossref_primary_10_1145_3070861 crossref_primary_10_1016_j_infsof_2022_106826 crossref_primary_10_1016_S1000_9361_11_60057_5 crossref_primary_10_1016_j_automatica_2023_110922 crossref_primary_10_1093_oxrep_grab017 crossref_primary_10_9746_sicetr_49_370 crossref_primary_10_1016_j_segan_2025_101627 crossref_primary_10_1109_TSE_2018_2880218 crossref_primary_10_1016_j_ijepes_2015_11_057 crossref_primary_10_1016_j_knosys_2011_09_008 crossref_primary_10_1007_s10458_019_09430_0 crossref_primary_10_1109_LCSYS_2024_3501155 crossref_primary_10_3724_SP_J_1004_2010_00289 crossref_primary_10_1109_ACCESS_2021_3053348 crossref_primary_10_1109_TMLCN_2023_3313988 crossref_primary_10_1140_epjb_e2010_00201_8 crossref_primary_10_1016_j_automatica_2016_02_002 crossref_primary_10_1109_TCNS_2021_3061909 crossref_primary_10_1049_joe_2019_1200 crossref_primary_10_1109_TMLCN_2024_3368367 crossref_primary_10_1016_j_knosys_2023_110459 crossref_primary_10_1371_journal_pone_0172395 crossref_primary_10_1016_j_simpa_2022_100421 crossref_primary_10_3389_frobt_2018_00134 crossref_primary_10_1016_j_cor_2013_02_024 crossref_primary_10_1109_TMC_2020_3033782 crossref_primary_10_1093_forsci_fxz012 crossref_primary_10_1016_j_asoc_2023_110758 crossref_primary_10_1109_TSG_2016_2607801 crossref_primary_10_1109_TAC_2021_3049345 crossref_primary_10_1016_j_egyr_2023_04_301 crossref_primary_10_1109_TWC_2022_3150429 crossref_primary_10_1109_ACCESS_2021_3113350 crossref_primary_10_1049_trit_2018_0001 crossref_primary_10_3389_frobt_2020_00018 crossref_primary_10_3390_app13074569 crossref_primary_10_3390_app15020836 crossref_primary_10_1109_JIOT_2019_2935543 crossref_primary_10_3390_s20123401 crossref_primary_10_1007_s11704_024_3797_6 crossref_primary_10_1109_TCYB_2016_2544866 crossref_primary_10_1109_LRA_2021_3102309 crossref_primary_10_1016_j_iot_2024_101436 crossref_primary_10_3390_electronics11071069 crossref_primary_10_1007_s11768_013_1141_z crossref_primary_10_1007_s40747_025_01788_x crossref_primary_10_3390_s23073625 crossref_primary_10_1007_s42979_023_02114_3 crossref_primary_10_32604_iasc_2024_047017 crossref_primary_10_1007_s10514_018_9719_4 crossref_primary_10_1016_j_renene_2022_03_153 crossref_primary_10_1109_TWC_2019_2919611 crossref_primary_10_1007_s11063_024_11705_x crossref_primary_10_1371_journal_pone_0127129 crossref_primary_10_1109_TNNLS_2022_3146201 crossref_primary_10_1186_s13638_015_0381_7 crossref_primary_10_1115_1_4038158 crossref_primary_10_1007_s40708_016_0042_6 crossref_primary_10_1016_j_comnet_2016_01_011 crossref_primary_10_1109_TCYB_2020_2977374 crossref_primary_10_3233_AIC_180596 crossref_primary_10_1109_ACCESS_2019_2930640 crossref_primary_10_1016_j_neucom_2022_06_091 crossref_primary_10_1016_j_jnlest_2024_100290 crossref_primary_10_2478_s13230_011_0017_5 crossref_primary_10_3390_rs15112893 crossref_primary_10_1016_j_jnca_2024_103834 crossref_primary_10_1109_LWC_2022_3228045 crossref_primary_10_1016_j_artint_2017_12_001 crossref_primary_10_1007_s10458_021_09506_w crossref_primary_10_1016_j_rser_2020_110618 crossref_primary_10_1109_JIOT_2019_2962915 crossref_primary_10_1109_TCYB_2014_2349152 crossref_primary_10_1016_j_jnca_2011_11_004 crossref_primary_10_1109_TCYB_2016_2634027 crossref_primary_10_1109_ACCESS_2020_2985932 crossref_primary_10_1109_TITS_2023_3303991 crossref_primary_10_1109_TCNS_2021_3124896 crossref_primary_10_1126_scirobotics_abo0235 crossref_primary_10_1016_j_ifacol_2023_10_1100 crossref_primary_10_1109_TMM_2023_3275853 crossref_primary_10_1016_j_trc_2011_11_014 crossref_primary_10_1109_TKDE_2020_3006084 crossref_primary_10_1155_2022_4401653 crossref_primary_10_1016_j_eswa_2013_01_035 crossref_primary_10_1016_j_ins_2016_05_002 crossref_primary_10_1109_TVT_2022_3203050 crossref_primary_10_1109_TVT_2021_3055511 crossref_primary_10_3390_electronics13152927 crossref_primary_10_1109_TSMC_2018_2865488 crossref_primary_10_1016_j_amc_2022_127819 crossref_primary_10_1109_TCYB_2014_2306919 crossref_primary_10_1016_j_trb_2022_02_006 crossref_primary_10_3390_s21082862 crossref_primary_10_3390_s23052373 crossref_primary_10_1109_COMST_2016_2539923 crossref_primary_10_1109_TNN_2011_2111384 crossref_primary_10_1103_PhysRevE_102_012402 crossref_primary_10_1016_j_engappai_2013_07_017 crossref_primary_10_1109_TAES_2024_3447609 crossref_primary_10_1109_ACCESS_2016_2565198 crossref_primary_10_1016_j_eswa_2021_115127 crossref_primary_10_1360_SSI_2023_0010 crossref_primary_10_1007_s10462_023_10450_2 crossref_primary_10_1080_10286608_2012_716424 crossref_primary_10_1108_IJIUS_12_2018_0036 crossref_primary_10_1109_TSG_2019_2909266 crossref_primary_10_1155_2023_4419907 crossref_primary_10_1111_1756_2171_12383 crossref_primary_10_1109_TCYB_2020_3006620 crossref_primary_10_1016_j_cja_2020_05_001 crossref_primary_10_1287_opre_2022_0291 crossref_primary_10_1109_TCDS_2019_2926477 crossref_primary_10_1016_j_eswa_2024_124959 crossref_primary_10_1109_ACCESS_2020_3027707 crossref_primary_10_1109_TBC_2023_3246815 crossref_primary_10_1155_2011_980216 crossref_primary_10_1007_s42979_024_03001_1 crossref_primary_10_1103_PhysRevX_12_011007 crossref_primary_10_1007_s43684_022_00029_z crossref_primary_10_1145_3712004 crossref_primary_10_1109_TIA_2023_3300290 crossref_primary_10_3390_s22218159 crossref_primary_10_1007_s10462_021_09997_9 crossref_primary_10_1109_TCYB_2015_2445744 crossref_primary_10_1177_1729881420960342 crossref_primary_10_1007_s10506_012_9134_7 crossref_primary_10_1038_s42256_023_00646_0 crossref_primary_10_1109_TMI_2020_3018508 crossref_primary_10_1186_s13326_017_0142_0 crossref_primary_10_3389_frai_2022_908353 crossref_primary_10_1109_TKDE_2022_3225109 crossref_primary_10_1007_s00521_017_3066_9 crossref_primary_10_1109_OJCOMS_2021_3056113 crossref_primary_10_1016_j_neucom_2024_128514 crossref_primary_10_1109_TSP_2013_2241057 crossref_primary_10_1145_3582081 crossref_primary_10_1016_j_egyr_2023_11_048 crossref_primary_10_1109_ACCESS_2020_3001311 crossref_primary_10_1109_TASE_2012_2229978 crossref_primary_10_1109_TWC_2022_3170308 crossref_primary_10_1109_TVT_2022_3196500 crossref_primary_10_1016_j_robot_2024_104631 crossref_primary_10_1109_TWC_2020_3003719 crossref_primary_10_1016_j_cobeha_2019_04_013 crossref_primary_10_1089_cmb_2021_0549 crossref_primary_10_3390_en15176488 crossref_primary_10_3390_app112210870 crossref_primary_10_3389_fnbot_2023_1302898 crossref_primary_10_1007_s00500_015_1607_7 crossref_primary_10_1038_s41598_022_20234_3 crossref_primary_10_1109_TPWRS_2014_2326403 crossref_primary_10_3390_app12168004 crossref_primary_10_3390_math12132102 crossref_primary_10_1016_j_watres_2019_115029 crossref_primary_10_1109_TMC_2016_2601926 crossref_primary_10_4236_jbise_2018_118018 crossref_primary_10_3390_electronics12122722 crossref_primary_10_1109_TITS_2021_3055899 crossref_primary_10_1109_TCAD_2022_3233019 crossref_primary_10_3390_s23198050 crossref_primary_10_1109_JIOT_2022_3168296 crossref_primary_10_1016_j_apenergy_2016_06_041 crossref_primary_10_1007_s00521_023_09136_1 crossref_primary_10_1109_TVT_2020_3006218 crossref_primary_10_1109_TVT_2019_2913695 crossref_primary_10_1145_3596444 crossref_primary_10_1007_s13218_013_0258_z crossref_primary_10_1109_TNNLS_2019_2946913 crossref_primary_10_1007_s10489_020_01832_y crossref_primary_10_1016_j_neucom_2017_01_076 crossref_primary_10_1109_TCCN_2020_2966604 crossref_primary_10_1016_j_ifacol_2020_12_2184 crossref_primary_10_1049_iet_com_2019_0900 crossref_primary_10_1109_ACCESS_2022_3227450 crossref_primary_10_1142_S0219525912500877 crossref_primary_10_1109_TII_2020_2977104 crossref_primary_10_1016_j_comcom_2023_12_002 crossref_primary_10_1109_ACCESS_2019_2942390 crossref_primary_10_1108_IMDS_10_2020_0566 crossref_primary_10_1016_j_ins_2019_07_094 crossref_primary_10_1016_j_conengprac_2021_104901 crossref_primary_10_1109_TPEL_2021_3089707 crossref_primary_10_1142_S0219525911002998 crossref_primary_10_1109_TCYB_2019_2906574 crossref_primary_10_1109_COMST_2020_2988367 crossref_primary_10_1002_sres_2865 crossref_primary_10_1002_wcm_2470 crossref_primary_10_1109_TITS_2020_3009289 crossref_primary_10_1007_s00500_019_04600_4 crossref_primary_10_1016_j_trc_2021_103122 crossref_primary_10_1142_S0219622012500277 crossref_primary_10_1145_3459991 crossref_primary_10_1016_j_media_2021_102193 crossref_primary_10_1049_cmu2_12800 crossref_primary_10_1109_ACCESS_2020_3040985 crossref_primary_10_1049_iet_cta_2018_6163 crossref_primary_10_1109_TCCN_2019_2950242 crossref_primary_10_1142_S1469026811003185 crossref_primary_10_1103_PhysRevE_105_045105 crossref_primary_10_1098_rsta_2024_0136 crossref_primary_10_1098_rsif_2020_0639 crossref_primary_10_1162_artl_a_00408 crossref_primary_10_2298_CSIS221210071A crossref_primary_10_1103_PhysRevE_106_054149 crossref_primary_10_1002_int_22594 crossref_primary_10_1016_j_neucom_2020_06_038 crossref_primary_10_1016_j_physa_2015_04_015 crossref_primary_10_1016_j_artint_2020_103356 crossref_primary_10_1016_j_cie_2021_107621 crossref_primary_10_1109_TCYB_2017_2647820 crossref_primary_10_1016_j_trc_2024_104702 crossref_primary_10_1016_j_trc_2024_104703 crossref_primary_10_1016_j_neucom_2021_12_025 crossref_primary_10_1007_s12065_012_0086_3 crossref_primary_10_1016_j_dt_2022_07_005 crossref_primary_10_1371_journal_pone_0282112 crossref_primary_10_1007_s00521_011_0624_4 crossref_primary_10_1016_j_jmsy_2020_06_010 crossref_primary_10_1098_rsta_2024_0148 crossref_primary_10_1109_TCYB_2020_3028267 crossref_primary_10_1109_JSTSP_2023_3239189 crossref_primary_10_1007_s40747_021_00499_3 crossref_primary_10_3390_s18124331 crossref_primary_10_1109_ACCESS_2024_3495032 crossref_primary_10_3390_robotics11020035 crossref_primary_10_1016_j_neucom_2020_06_040 crossref_primary_10_1109_JSTSP_2011_2176916 crossref_primary_10_1016_j_ifacol_2021_06_067 crossref_primary_10_2139_ssrn_4096569 crossref_primary_10_1109_JSTSP_2013_2259797 crossref_primary_10_1007_s43154_021_00063_4 crossref_primary_10_1109_ACCESS_2021_3058388 crossref_primary_10_1109_MSP_2014_2338894 crossref_primary_10_1109_TAI_2022_3207112 crossref_primary_10_1103_PhysRevE_102_012601 crossref_primary_10_1145_3054912 crossref_primary_10_1007_s10458_023_09628_3 crossref_primary_10_1016_j_physa_2021_126268 crossref_primary_10_1007_s11432_019_2825_y crossref_primary_10_1109_TITS_2024_3370820 crossref_primary_10_1109_TNNLS_2018_2832025 crossref_primary_10_1038_s42256_019_0064_x crossref_primary_10_1007_s12204_024_2713_4 crossref_primary_10_1016_j_eswa_2024_124117 crossref_primary_10_1109_TSMCA_2012_2183349 crossref_primary_10_1016_j_ifacol_2020_12_1290 crossref_primary_10_1177_03611981221093324 crossref_primary_10_1109_JIOT_2023_3263909 crossref_primary_10_3390_aerospace9060294 crossref_primary_10_3390_e24060774 crossref_primary_10_1016_j_future_2020_09_002 crossref_primary_10_1016_j_promfg_2020_01_312 crossref_primary_10_1007_s10458_013_9242_0 crossref_primary_10_1177_14613484211032758 crossref_primary_10_1109_TII_2022_3173928 crossref_primary_10_1080_1350486X_2022_2136727 crossref_primary_10_1002_tee_23034 |
| Cites_doi | 10.1142/9789812817471_0003 10.1007/3-540-45603-1_56 10.1080/1019678032000062212 10.1007/BF00114731 10.1023/A:1008942012299 10.1016/B978-1-55860-335-6.50027-1 10.1006/ijhc.1997.0160 10.1016/S0921-8890(03)00040-X 10.1145/1015330.1015445 10.1016/B978-1-55860-141-3.50030-4 10.1145/860575.860686 10.1023/A:1017992615625 10.1007/BF00115009 10.1145/1015330.1015410 10.1007/BF00992698 10.1007/BF00114724 10.1145/1102351.1102462 10.1016/S1389-0417(01)00015-8 10.1023/A:1007562506751 10.1016/B978-1-55860-307-3.50049-6 10.1016/B978-1-55860-377-6.50040-2 10.1145/301136.301195 10.1023/A:1007694015589 10.1162/neco.1994.6.6.1185 10.1023/A:1008819414322 10.1007/s10994-005-0461-8 10.1007/3-540-60923-7_25 10.1007/BF02481502 10.1137/040614384 10.1109/TSMC.1983.6313077 10.1007/s10458-006-7035-4 10.1007/BF00993306 10.1023/A:1008921914343 10.1613/jair.898 10.1007/BF00993104 10.1613/jair.121 10.1007/s10458-005-3783-9 10.1016/j.robot.2004.08.003 10.1007/3-540-44826-8_13 10.1287/opre.39.1.162 10.1109/IJCNN.2000.859399 10.1023/A:1017928328829 10.1162/jmlr.2003.4.6.1107 10.1109/COEC.2003.1210269 10.1017/CBO9780511806292 10.1016/j.engappai.2004.02.004 10.1002/9780470316887 10.1007/3-540-60923-7_18 10.1093/oso/9780195099713.001.0001 10.1023/A:1007518724497 10.1145/544741.544831 10.1007/s10458-006-9010-5 10.1007/11589990_19 10.1023/A:1007570708568 10.1162/jmlr.2003.4.6.1039 10.1007/3-540-44637-0_8 10.1613/jair.301 10.1023/A:1015504423309 10.1017/S026988890500041X 10.1023/A:1008945119734 10.1007/s10994-006-0143-1 10.1109/TEVC.2006.880330 10.1007/3-540-46146-9_16 10.1016/S0004-3702(02)00121-2 10.1109/9.580874 10.1613/jair.1024 10.1109/5326.897075 10.1007/s10458-005-2631-2 |
| ContentType | Journal Article |
| DBID | 97E RIA RIE AAYXX CITATION 7SC 7SP 7TB 8FD F28 FR3 JQ2 L7M L~C L~D |
| DOI | 10.1109/TSMCC.2007.913919 |
| DatabaseName | IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database ANTE: Abstracts in New Technology & Engineering Engineering Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | Technology Research Database |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Sciences (General) Economics |
| EISSN | 1558-2442 |
| EndPage | 172 |
| ExternalDocumentID | 10_1109_TSMCC_2007_913919 4445757 |
| Genre | orig-research |
| GroupedDBID | -~X 0R~ 29I 4.4 5VS 6IK 97E AAJGR AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFS AETIX AGQYO AGSQL AHBIQ AI. AIBXA ALLEH ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ EBS EJD F5P HZ~ H~9 IFIPE IFJZH IPLJI JAVBF LAI M43 O9- OCL PZZ RIA RIE RNS VH1 AAYOK AAYXX CITATION RIG 7SC 7SP 7TB 8FD F28 FR3 JQ2 L7M L~C L~D |
| ID | FETCH-LOGICAL-c324t-cfcd2ef993c03c75ca6ed892604faa15b0c749fbf9a1f7d7ea9111b6ce5b596a3 |
| IEDL.DBID | RIE |
| ISSN | 1094-6977 |
| IngestDate | Thu Jul 10 23:28:27 EDT 2025 Tue Jul 01 03:52:40 EDT 2025 Thu Apr 24 22:54:10 EDT 2025 Wed Aug 27 06:03:30 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 2 |
| Keywords | Distributed control game theory multiagent systems reinforcement learning |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c324t-cfcd2ef993c03c75ca6ed892604faa15b0c749fbf9a1f7d7ea9111b6ce5b596a3 |
| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
| PQID | 875050829 |
| PQPubID | 23500 |
| PageCount | 17 |
| ParticipantIDs | ieee_primary_4445757 proquest_miscellaneous_875050829 crossref_citationtrail_10_1109_TSMCC_2007_913919 crossref_primary_10_1109_TSMCC_2007_913919 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2008-03-01 |
| PublicationDateYYYYMMDD | 2008-03-01 |
| PublicationDate_xml | – month: 03 year: 2008 text: 2008-03-01 day: 01 |
| PublicationDecade | 2000 |
| PublicationTitle | IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews |
| PublicationTitleAbbrev | TSMCC |
| PublicationYear | 2008 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| References | zinkevich (ref67) 0 oo (ref104) 0 price (ref53) 2003; 19 ref54 riedmiller (ref93) 2000 weinberg (ref73) 0 spiros kapetanakis (ref63) 2004 ref51 fudenberg (ref12) 1998 sen (ref6) 1999 kaelbling (ref8) 1996; 4 ref46 fischer (ref81) 0 ref47 ref44 ref43 bowling (ref88) 0 ref49 ref4 knnen (ref72) 0 ref5 ref101 ref35 ref34 ref37 ref36 spaan (ref79) 1 ref33 ref32 greenwald (ref42) 0 ref39 ref38 bowling (ref59) 2000 sen (ref69) 0 singh (ref66) 0 hansen (ref131) 0 fernndez (ref95) 2001; 16 shoham (ref14) 2003 claus (ref62) 0 pynadath (ref78) 2002; 16 ref26 ref25 ref20 ref22 ref28 ref27 buoniu (ref50) 0 (ref77) 0 matari (ref86) 1996 carmel (ref76) 1996 ref13 jong (ref16) 2005 wiering (ref91) 0 ref128 ref129 wiering (ref98) 1999; 7 ref97 bertsekas (ref30) 2005; 1 ref127 ref96 ref125 ref17 (ref1) 1999 potter (ref18) 1994 haynes (ref21) 0 vlassis (ref2) 2003 chalkiadakis (2003 mar ) (ref58) 2003 boutilier (ref80) 0 ref132 ref94 ref130 ref90 tuyls (ref99) 0 tesauro (ref68) 0; 16 boyan (ref108) 0; 6 matari (ref70) 1997; 4 hsu (ref102) 0; 2132 ref87 matari (ref85) 0 knnen (ref24) 0 ficici (ref19) 2000 kok (ref83) 0 powers (ref55) 0; 17 bck (ref15) 1996 hu (ref40) 0 basar (ref11) 1999 kok (ref48) 2005 ref82 schaerf (ref107) 1995; 2 miconi (ref23) 0 ref106 ref75 ref74 ref105 (ref10) 1999 guestrin (ref45) 0 bakker (ref92) 3 ref103 parunak (ref3) 1999 choi (ref109) 0; 8 price (ref126) 0 brown (ref65) 1951 bertsekas (ref111) 1996 lauer (ref41) 0 ernst (ref120) 2005; 6 ref112 ref110 crites (ref71) 1996; 8 bowling (ref61) 2003 bowling (ref56) 2001 sutton (ref7) 1998 nash (ref84) 1996 ref119 ref117 merke (ref100) 0; 2377 ref118 ref115 ref116 ref113 ref114 bertsekas (ref29) 2001; 2 wang (ref64) 0; 15 littman (ref89) 0 clouse (ref52) 0 puterman (ref31) 1994 cherkassky (ref9) 1998 buoniu (ref124) 0 ref60 ref122 ref123 ref121 bowling (ref57) 0; 17 |
| References_xml | – year: 1999 ident: ref11 publication-title: Dynamic Noncooperative Game Theory – ident: ref26 doi: 10.1142/9789812817471_0003 – start-page: 467 year: 2000 ident: ref19 article-title: a game-theoretic approach to the simple coevolutionary algorithm publication-title: Proc 6th Int Conf Parallel Probl Solving Nat (PPSN-VI) – volume: 2377 start-page: 435 year: 0 ident: ref100 article-title: karlsruhe brainstormers---a reinforcement learning approach to robotic soccer publication-title: Robot Soccer World Cup V (RoboCup 2001) doi: 10.1007/3-540-45603-1_56 – start-page: 68 year: 0 ident: ref24 article-title: gradient based method for symmetric and asymmetric multiagent reinforcement learning publication-title: Proc 4th Int Conf Intell Data Eng Autom Learn (IDEAL-03) – ident: ref101 doi: 10.1080/1019678032000062212 – start-page: 746 year: 0 ident: ref62 article-title: the dynamics of reinforcement learning in cooperative multiagent systems publication-title: Proc 15th Nat Conf Artif Intell 10th Conf Innov Appl Artif Intell (AAAI/IAAI-98) – ident: ref33 doi: 10.1007/BF00114731 – ident: ref4 doi: 10.1023/A:1008942012299 – start-page: 137 year: 2000 ident: ref93 publication-title: Balancing Reactivity and Social Deliberation in Multi-Agent Systems – ident: ref39 doi: 10.1016/B978-1-55860-335-6.50027-1 – ident: ref82 doi: 10.1006/ijhc.1997.0160 – year: 1998 ident: ref9 publication-title: Learning From Data – start-page: 1347 year: 0 ident: ref124 article-title: decentralized reinforcement learning control of a robotic manipulator publication-title: Proc 9th Int Conf Control Autom Robot Vis (ICARCV-06) – ident: ref96 doi: 10.1016/S0921-8890(03)00040-X – year: 3 ident: ref92 article-title: cooperative multi-agent reinforcement learning of traffic lights publication-title: Workshop Coop Multi-Agent Learn 16th Eur Conf Mach Learn (ECML-05) – year: 1998 ident: ref7 publication-title: Reinforcement Learning An Introduction – ident: ref119 doi: 10.1145/1015330.1015445 – ident: ref36 doi: 10.1016/B978-1-55860-141-3.50030-4 – ident: ref74 doi: 10.1145/860575.860686 – start-page: 1021 year: 2001 ident: ref56 article-title: rational and convergent learning in stochastic games publication-title: Proc 17th Int Conf Artif Intell (IJCAI-01) – ident: ref114 doi: 10.1023/A:1017992615625 – year: 2005 ident: ref16 publication-title: Evolutionary Computation A Unified Approach – start-page: 1258 year: 2004 ident: ref63 article-title: Reinforcement learning of coordination in heterogeneous cooperative multi-agent systems publication-title: the Third International Joint Conference on Autonomous Agents and Multiagent Systems 2004 AAMAS 2004 – year: 2003 ident: ref58 publication-title: Multiagent reinforcement learning Stochastic games with multiple learning players – start-page: 535 year: 0 ident: ref41 article-title: an algorithm for distributed reinforcement learning in cooperative multi-agent systems publication-title: Proc 17th Int Conf Mach Learn (ICML-00) – volume: 15 start-page: 1571 year: 0 ident: ref64 article-title: reinforcement learning to play an optimal nash equilibrium in team markov games publication-title: Proc Adv Neural Inf Process Syst (NIPS-02) – volume: 6 start-page: 503 year: 2005 ident: ref120 article-title: tree-based batch mode reinforcement learning publication-title: J Mach Learn Res – ident: ref34 doi: 10.1007/BF00115009 – start-page: 66 year: 1 ident: ref79 article-title: high level coordination of agents based on multiagent markov decision processes with roles publication-title: Proc Workshop Coop Robot 2002 IEEE/RSJ Int Conf Intell Robots Syst (IROS-02) – volume: 1 year: 2005 ident: ref30 publication-title: Dynamic Programming and Optimal Control – volume: 8 start-page: 1017 year: 1996 ident: ref71 article-title: improving elevator performance using reinforcement learning publication-title: Proc Adv Neural Inf Process Syst (NIPS-95) – ident: ref47 doi: 10.1145/1015330.1015410 – ident: ref32 doi: 10.1007/BF00992698 – ident: ref113 doi: 10.1007/BF00114724 – start-page: 259 year: 1999 ident: ref6 publication-title: Multiagent Systems A Modern Approach to Distributed Artificial Intelligence – ident: ref116 doi: 10.1145/1102351.1102462 – ident: ref38 doi: 10.1016/S1389-0417(01)00015-8 – start-page: 226 year: 0 ident: ref99 article-title: q-learning in simulated robotic soccer---large state spaces and incomplete information publication-title: Proc 2002 Int Conf Mach Learn Appl (ICMLA-02) – ident: ref25 doi: 10.1023/A:1007562506751 – year: 1996 ident: ref111 publication-title: Neuro-Dynamic Programming – start-page: 195 year: 0 ident: ref80 article-title: planning, learning and coordination in multiagent decision processes publication-title: Proc 6th Conf Theor Aspects Rationality Knowl (TARK-96) – ident: ref51 doi: 10.1016/B978-1-55860-307-3.50049-6 – ident: ref112 doi: 10.1016/B978-1-55860-377-6.50040-2 – ident: ref97 doi: 10.1145/301136.301195 – volume: 16 year: 0 ident: ref68 article-title: extending q-learning to general adaptive multi-agent systems publication-title: Proc Adv Neural Inf Process Syst (NIPS-03) – ident: ref122 doi: 10.1023/A:1007694015589 – start-page: 96 year: 0 ident: ref89 article-title: implicit negotiation in repeated games publication-title: Proc 8th Int Workshop Agent Theories Arch Lang (ATAL-2001) – start-page: 271 year: 0 ident: ref21 article-title: strongly typed genetic programming in evolving cooperation strategies publication-title: Proceedings of the 6th International Conference on Genetic Algorithms (ICGA6) – ident: ref43 doi: 10.1162/neco.1994.6.6.1185 – volume: 4 start-page: 73 year: 1997 ident: ref70 article-title: reinforcement learning in the multi-robot domain publication-title: Auton Robots doi: 10.1023/A:1008819414322 – ident: ref130 doi: 10.1007/s10994-005-0461-8 – start-page: 152 year: 1996 ident: ref86 publication-title: Adaptation and Learning in Multi-Agent Systems doi: 10.1007/3-540-60923-7_25 – ident: ref125 doi: 10.1007/BF02481502 – ident: ref115 doi: 10.1137/040614384 – year: 1996 ident: ref84 publication-title: Linear and Nonlinear Programming – ident: ref35 doi: 10.1109/TSMC.1983.6313077 – ident: ref128 doi: 10.1007/s10458-006-7035-4 – year: 1998 ident: ref12 publication-title: The Theory of Learning in Games – ident: ref44 doi: 10.1007/BF00993306 – volume: 7 start-page: 77 year: 1999 ident: ref98 article-title: reinforcement learning soccer teams with incomplete world models publication-title: Auton Robots doi: 10.1023/A:1008921914343 – volume: 19 start-page: 569 year: 2003 ident: ref53 article-title: accelerating reinforcement learning through implicit imitation publication-title: J Artif Intell Res doi: 10.1613/jair.898 – start-page: 374 year: 1951 ident: ref65 publication-title: Activitiy Analysis of Production and Allocation – start-page: 426 year: 0 ident: ref69 article-title: learning to coordinate without sharing information publication-title: Proc 12th Nat Conf Artif Intell (AAAI-94) – year: 0 ident: ref77 publication-title: W T Uther and M Veloso (1997 Apr ) Adversarial reinforcement learning School Comput Sci Carnegie Mellon Univ Pittsburgh PA Tech Rep [Onlilne] Available http //www cs cmu edu/afs/cs/user/will/www/papers/Uther97a ps – start-page: 242 year: 0 ident: ref40 article-title: multiagent reinforcement learning: theoretical framework and an algorithm publication-title: Proc 15th Int Conf Mach Learn (ICML-98) – start-page: 451 year: 0 ident: ref104 article-title: stock trading system using reinforcement learning with cooperative agents publication-title: Proc 19th Int Conf Mach Learn (ICML-02) – ident: ref37 doi: 10.1007/BF00993104 – year: 2003 ident: ref2 publication-title: A concise introduction to multiagent systems and distributed AI – year: 2000 ident: ref59 publication-title: ``An analysis of stochastic game theory for multiagent reinforcement learning '' – year: 1999 ident: ref10 publication-title: Unsupervised Learning Foundations of Neural Computation – year: 2005 ident: ref48 article-title: using the max-plus algorithm for multiagent decision making in coordination graphs publication-title: Robot Soccer World Cup IX (RoboCup 2005) – start-page: 89 year: 0 ident: ref88 article-title: convergence problems of general-sum multiagent reinforcement learning publication-title: Proc 17th Int Conf Mach Learn (ICML-00) – start-page: 325 year: 0 ident: ref126 article-title: implicit imitation in multiagent reinforcement learning publication-title: Proc 16th Int Conf Mach Learn (ICML-99) – start-page: 1151 year: 0 ident: ref91 article-title: multi-agent reinforcement learning for traffic light control publication-title: Proc 17th Int Conf Mach Learn (ICML-00) – volume: 2 start-page: 475 year: 1995 ident: ref107 article-title: adaptive load balancing: a study in multi-agent learning publication-title: J Artif Intell Res doi: 10.1613/jair.121 – ident: ref87 doi: 10.1007/s10458-005-3783-9 – start-page: 35 year: 0 ident: ref50 article-title: multiagent reinforcement learning with adaptive state focus publication-title: Proc 17th Belgian--Dutch Conf Artif Intell (BNAIC-05) – ident: ref46 doi: 10.1016/j.robot.2004.08.003 – ident: ref132 doi: 10.1007/3-540-44826-8_13 – ident: ref129 doi: 10.1287/opre.39.1.162 – ident: ref90 doi: 10.1109/IJCNN.2000.859399 – ident: ref118 doi: 10.1023/A:1017928328829 – start-page: 29 year: 0 ident: ref83 article-title: utile coordination: learning interdependencies among cooperative agents publication-title: Proc IEEE Symp Comput Intell Games (CIG-05) – ident: ref121 doi: 10.1162/jmlr.2003.4.6.1107 – volume: 8 start-page: 945 year: 0 ident: ref109 article-title: predictive q-routing: a memory-based reinforcement learning approach to adaptive traffic control publication-title: Proc Adv Neural Inf Process Syst (NIPS-95) – ident: ref106 doi: 10.1109/COEC.2003.1210269 – start-page: 227 year: 0 ident: ref45 article-title: coordinated reinforcement learning publication-title: Proc 19th Int Conf Mach Learn (ICML-02) – ident: ref27 doi: 10.1017/CBO9780511806292 – ident: ref110 doi: 10.1016/j.engappai.2004.02.004 – year: 1994 ident: ref31 publication-title: Markov Decision Processes---Discrete Stochastic Dynamic Programming doi: 10.1002/9780470316887 – start-page: 40 year: 1996 ident: ref76 publication-title: Adaptation and Learning in Multi-Agent Systems doi: 10.1007/3-540-60923-7_18 – year: 1996 ident: ref15 publication-title: Evolutionary Algorithms in Theory and Practice Evolution Strategies Evolutionary Programming Genetic Algorithms doi: 10.1093/oso/9780195099713.001.0001 – ident: ref5 doi: 10.1023/A:1007518724497 – year: 1999 ident: ref1 publication-title: Multiagent Systems A Modern Approach to Distributed Artificial Intelligence – ident: ref75 doi: 10.1145/544741.544831 – start-page: 709 year: 0 ident: ref131 article-title: dynamic programming for partially observable stochastic games publication-title: Proc 19th Natl Conf Artif Intell (AAAI-04) – ident: ref127 doi: 10.1007/s10458-006-9010-5 – ident: ref49 doi: 10.1007/11589990_19 – year: 2003 ident: ref14 publication-title: Multi-agent reinforcement learning A critical survey – start-page: 336 year: 0 ident: ref72 article-title: asymmetric multiagent reinforcement learning publication-title: Proc IEEE/WIC Int Conf Intell Agent Technol (IAT-03) – start-page: 377 year: 1999 ident: ref3 publication-title: Multi-Agent Systems A Modern Approach to Distributed Artificial Intelligence – start-page: 1334 year: 0 ident: ref81 article-title: hierarchical reinforcement learning in communication-mediated multiagent coordination publication-title: Proc 3rd Int Joint Conf Autonomous Agents and Multiagent Systems (AAMAS) – ident: ref22 doi: 10.1023/A:1007570708568 – volume: 17 start-page: 1089 year: 0 ident: ref55 article-title: new criteria and a new algorithm for learning in multi-agent systems publication-title: Proc Adv Neural Inf Process Syst (NIPS-04) – year: 2003 ident: ref61 publication-title: Multiagent learning in the presence of agents with limitations – start-page: 249 year: 1994 ident: ref18 article-title: a cooperative coevolutionary approach to function optimization publication-title: Proc 3rd Conf Parallel Probl Solving Nat (PPSN-III) – ident: ref54 doi: 10.1162/jmlr.2003.4.6.1039 – volume: 2132 start-page: 108 year: 0 ident: ref102 article-title: market performance of adaptive trading agents in synchronous double auctions publication-title: Proc 4th Pacific Rim Int Workshop Multi-Agents Intell Agents Specification Model Appl (PRIMA-01) doi: 10.1007/3-540-44637-0_8 – year: 0 ident: ref52 article-title: learning from an automated training agent publication-title: Workshop Agents that Learn from Other Agents 12th Int Conf Mach Learn (ICML-95) – start-page: 242 year: 0 ident: ref42 article-title: correlated-q learning publication-title: Proc 20th Int Conf Mach Learn (ICML-03) – volume: 4 start-page: 237 year: 1996 ident: ref8 article-title: reinforcement learning: a survey publication-title: J Artif Intell Res doi: 10.1613/jair.301 – ident: ref105 doi: 10.1023/A:1015504423309 – start-page: 541 year: 0 ident: ref66 article-title: nash convergence of gradient dynamics in general-sum games publication-title: Proc 16th Conf Uncertainty Artif Intell (UAI-00) – start-page: 928 year: 0 ident: ref67 article-title: online convex programming and generalized infinitesimal gradient ascent publication-title: Proc 20th Int Conf Mach Learn (ICML-03) – volume: 17 start-page: 209 year: 0 ident: ref57 article-title: convergence and no-regret in multiagent learning publication-title: Proc Adv Neural Inf Process Syst (NIPS-04) – ident: ref28 doi: 10.1017/S026988890500041X – volume: 2 year: 2001 ident: ref29 publication-title: Dynamic Programming and Optimal Control – ident: ref94 doi: 10.1023/A:1008945119734 – ident: ref60 doi: 10.1007/s10994-006-0143-1 – ident: ref20 doi: 10.1109/TEVC.2006.880330 – ident: ref103 doi: 10.1007/3-540-46146-9_16 – start-page: 181 year: 0 ident: ref85 article-title: reward functions for accelerated learning publication-title: Proc 11th Int Conf Mach Learn (ICML-94) – volume: 16 start-page: 217 year: 2001 ident: ref95 article-title: learning in large cooperative multi-robot systems publication-title: Int J Robot Autom – start-page: 647 year: 0 ident: ref23 article-title: when evolving populations is better than coevolving individuals: the blind mice problem publication-title: Proc 18th Int Joint Conf Artif Intell (IJCAI-03) – ident: ref13 doi: 10.1016/S0004-3702(02)00121-2 – ident: ref117 doi: 10.1109/9.580874 – volume: 16 start-page: 389 year: 2002 ident: ref78 article-title: the communicative multiagent team decision problem: analyzing teamwork theories and models publication-title: J Artif Intell Res doi: 10.1613/jair.1024 – ident: ref123 doi: 10.1109/5326.897075 – volume: 6 start-page: 671 year: 0 ident: ref108 article-title: packet routing in dynamically changing networks: a reinforcement learning approach publication-title: Proc Adv Neural Inf Process Syst (NIPS-93) – ident: ref17 doi: 10.1007/s10458-005-2631-2 – start-page: 506 year: 0 ident: ref73 article-title: best-response multiagent learning in non-stationary environments publication-title: Proc 3rd Int Joint Conf Autonomous Agents and Multiagent Systems (AAMAS) |
| SSID | ssj0014493 |
| Score | 2.4939144 |
| SecondaryResourceType | review_article |
| Snippet | Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The... |
| SourceID | proquest crossref ieee |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 156 |
| SubjectTerms | Algorithms Control systems Cybernetics Distributed control Economics Environmental economics Feedback game theory Learning Marine technology Marl Mechanical engineering Multiagent systems Reinforcement reinforcement learning Resource management Robots Tasks |
| Title | A Comprehensive Survey of Multiagent Reinforcement Learning |
| URI | https://ieeexplore.ieee.org/document/4445757 https://www.proquest.com/docview/875050829 |
| Volume | 38 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3dS8MwED_mnvRB3aY4v8iDDyp2a9e0WfFpDMcQ5oPbYG8lSa8KyirbKuhfbz66MlTEtxYSCHfJ5Xe5u98BXPiCdpCjcKQnhUOVh-KIEBOHCQUOhMSUmSSa0UM4nNL7WTCrwE1ZC4OIJvkMW_rTxPKTTOb6qaxNKVXogm3BlnLcbK1WGTGgNLLJ9BF1QgVqigim-m9PxqN-37IVahJMTaqzcQeZpio_LLG5XgZ7MFovzGaVvLTylWjJz2-cjf9d-T7sFjiT9OzGqEEF53XY2WAfrEOtONdLclmQT1814LZHtIlY4LPNbCfjfPGOHyRLianV5boUizyiIVyV5m2RFBytTwcwHdxN-kOnaLDgSIWjVo5MZdLBVEEU6fqSBZIrNXUj5eLQlHMvEK5kNEpFGnEvZQlDrk2jCCUGIohC7h9CdZ7N8QiIQIaJzxWcY6gp2LQ18EWCCj52JXa9JrhrkceyYB_XTTBeY-OFuFFstKS7YrLYaqkJ1-WUN0u98dfghpZ6ObAQeBPIWq-xOjc6GMLnmOXLWPlpbqALi49_n3kC2zY1RKebnUJ1tcjxTOGPlTg3G-8LyhjXsg |
| linkProvider | IEEE |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3dS8MwED90PqgP6jbF-ZkHH1TsbG3arPg0hmPqtge3gW8lSa8KyibbKuhfbz66MVTEtxYSCLnk7ne5u98BnPiCXiFH4UhPCocqD8URISYOEwocCIkpM0k0nW7YGtC7x-BxCS7mtTCIaJLPsKo_TSw_GclMP5VdUkoVumDLsKLsfuDZaq15zIDSyKbTR9QJFazJY5jq_7Lf6zQalq9Q02BqWp0FK2TaqvzQxcbANDehM1uazSt5qWZTUZWf31gb_7v2LdjIkSap26NRhCUclmB9gX-wBMX8Zk_IaU4_fVaG6zrRSmKMzza3nfSy8Tt-kFFKTLUu18VY5AEN5ao0r4skZ2l92oZB86bfaDl5iwVHKiQ1dWQqkytMFUiRri9ZILkSVC1STg5NOfcC4UpGo1SkEfdSljDkWjmKUGIggijk_g4UhqMh7gIRyDDxuQJ0DDUJm9YHvkhQAciaxJpXAXe25bHM-cd1G4zX2PghbhQbKem-mCy2UqrA-XzKmyXf-GtwWe_6fGC-4RUgM7nG6ubocAgf4iibxMpTcwNdWrz3-8xjWG31O-24fdu934c1myiik88OoDAdZ3io0MhUHJlD-AU00dr7 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Comprehensive+Survey+of+Multiagent+Reinforcement+Learning&rft.jtitle=IEEE+transactions+on+systems%2C+man+and+cybernetics.+Part+C%2C+Applications+and+reviews&rft.au=Busoniu%2C+L.&rft.au=Babuska%2C+R.&rft.au=De+Schutter%2C+B.&rft.date=2008-03-01&rft.pub=IEEE&rft.issn=1094-6977&rft.volume=38&rft.issue=2&rft.spage=156&rft.epage=172&rft_id=info:doi/10.1109%2FTSMCC.2007.913919&rft.externalDocID=4445757 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1094-6977&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1094-6977&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1094-6977&client=summon |