FUZZY LOGIC APPROACHES TO COOPERATIVE STRATEGIES IN MULTI-AGENT GAME THEORY

The primary objective of this book is to explore decision-making processes in complex environments where individuals must balance self-interest and cooperation, utilizing fuzzy logic to capture uncertainties in real-world scenarios. It focuses on creating a fuzzy logic-based model of payoffs in iterated Prisoner's Dilemma games by defining fuzzy sets, establishing rules mapping decisions to satisfaction levels, and using a fuzzy inference system for analysis. The Mean of Maximum defuzzification method is applied to determine crisp values for variables like "Satisfaction," and the TOPSIS technique is used to rank alternatives in the game, aiming to identify optimal strategies for players. Overall, the study sheds light on decision-making strategies in multi-agent settings and showcases how fuzzy logic can improve the modeling of complex decision processes involving the balance between self-interest and cooperation. Chapter 1 describes various essential topics concerning decision-making strategies in multi-agent environments using fuzzy logic. It begins by introducing the classic concept of the Prisoner's Dilemma, a game theory scenario that examines decision-making and cooperation among rational individuals. The chapter further explores the iterated version of the Prisoner's Dilemma, where the game is played repeatedly to observe long-term strategies and outcomes. Additionally, it introduces fuzzy sets to represent uncertainty and vagueness in decision-making processes and discusses the application of fuzzy inference systems, particularly Mamdani Fuzzy Inference Systems, in modelling decision-making strategies in multi-agent settings. The concept of defuzzification is explained as a process to convert fuzzy output into crisp values for decision-making. The chapter also introduces the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) procedure, a method for ranking alternatives in multi-criteria decision-making based on their proximity to ideal solutions. Chapter 2 explains how fuzzy logic is utilized to model decision-making strategies in multi-agent environments, particularly focusing on cooperative behaviour in Iterated Prisoner's Dilemma games. It outlines the steps involved in developing a fuzzy logic-based model, defining fuzzy sets, and applying the TOPSIS procedure to analyse and rank strategies for optimal decision-making outcomes. We would like to thank the contributors for their rigorous scholarship and the institutional support that made this synthesis possible. I extend gratitude to publisher, reviewers, and collaborators whose expertise shaped this volume.