Indirect co-evolution for understanding belief in an incomplete information dynamic game

This study aims to design a new co-evolution algorithm, Mixture Co-evolution which enables modeling of integration and composition of direct co-evolution and indirect coevolution. This algorithm is applied to investigate properties of players' belief and of information incompleteness in a dynamic game. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning--Concept learning, Knowledge acquisition; I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search--Heuristic methods General Terms Algorithms, Design, Experimentation Keywords Co-evolution, Game theory, Belief, Incomplete Information

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Nanlin Jin
• Keywords: Artificial Intelligence, Co-evolution, GECCO 2006, Mixture Co-evolution, Optimization