Games with incomplete information and uncertain payoff: from the perspective of uncertainty theory

• Published in: Soft computing (Berlin, Germany) Vol. 23; no. 24; pp. 13669 - 13678
• Main Authors: Li, Yuchen, Yang, Zaoli
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2019; Springer Nature B.V
• Subjects: Artificial Intelligence; Bayesian analysis; Computational Intelligence; Control; Decision making; Engineering; Equilibrium; Game theory; Games; Literature reviews; Mathematical Logic and Foundations; Mechatronics; Methodologies and Application; Players; Preferences; Probability distribution; Probability theory; Robotics; Statistical analysis; Subject specialists; Theorems; Uncertainty; Uncertain equilibrium; Incomplete information; Game theory; Uncertainty theory

In a game with incomplete information, players do not possess full information about their opponents. For such a game, Bayesian approaches which are based on probability theory were employed to find the equilibria. Sometimes, players are lack of data for probabilistic reasoning in which case Bayesia...