Artificial Agentss

• Published in: X-Machines for Agent-Based Modeling Vol. 1; pp. 17 - 42
• Main Author: Kiran, Mariam
• Format: Book Chapter
• Language: English
• Published: CRC Press 2017
• Edition: 1
• Subjects: Markov Decision Processes; Match Parallelism; Closing Channels; MPI Library; MPI; Evolutionary Computation; Agent Architectures; Simulation Program Generator; Feed Forward Network Structure; ABM; Artificial Society; Cellular Automata; Gaussian Adaptation; Turing Machine; Symbolic Ai; Neural Adaptive Control; Ma; Memetic Algorithms; GAs; Evolutionary Algorithms; Monomorium Pharaonis; Agent Based Modeling Frameworks; LCS
• ISBN: 1498723853; 9781498723855
• DOI: 10.1201/9781315370729-2

Engineers and researchers are continually trying to copy or mimic real natural systems to study how they behave. This can allow the design of efficient computer networks or simulate robotic teams to help with disaster recovery in earthquake scenarios. Evolutionary computation is a sub-field under artificial intelligence (AI) research area, involving optimization to automatically solve difficult problems. Evolutionary computation contains four sub-topics: genetic algorithms, evolutionary programming, genetic programming and evolutionary strategies. Message Passing Interface (MPI) is a programming technique used in parallel programming that allows messages from different agents to communicate easily across different processors and platforms. This chapter focuses on agents which can be designed as either a logical machine with a set of actions or with artificial intelligence, as a set of controllers associated with actions, or with psychology, to mimic minds of real people. Multi-agent systems are temporal systems that are highly dependent on time steps.