Chapter 1 Introduction 1.1 Reinforcement Learning 1.1.1 Generality of Reinforcement Learning 1.1.2 Reinforcement Learning on Markov Decision Processes 1.1.3 Integrating Reinforcement Learning into Agent Architecture 1.2 Multiagent Reinforcement Learning 1.2.1 Multiagent Systems 1.2.2 Reinforcement Learning in Multiagent Systems 1.2.3 Learning and Coordination in Multiagent Systems 1.3 Ant System for Stochastic Combinatorial Optimization 1.3.1 Ants Forage Behavior 1.3.2 Ant Colony Optimization 1.3.3 MAX-MIN Ant System 1.4 Motivations and Consequences 1.5 Book Summary BibliographyChapter 2 Reinforcement Learning and Its Combination with Ant Colony System 2.1 Introduction 2.2 Investigation into Reinforcement Learning and Swarm Intelligence 2.2.1 Temporal Differences Learning Method 2.2.2 Active Exploration and Experience Replay in Reinforcement Learning 2.2.3 Ant Colony System for Traveling Salesman Problem 2.3 The Q-ACS Multiagent Learning Method 2.3.1 The Q-ACS Learning Algorithm 2.3.2 Some Properties of the Q-ACS Learning Method 2.3.3 Relation with Ant-Q Learning Method 2.4 Simulations and Results 2.5 Conclusions BibliographyChapter ……
