This monograph investigates the fundamental roles of intention recognition and commitment in the evolution of cooperative behavior. The book analyzes intention recognition from artificial intelligence and evolutionary computational modeling perspectives, proposing a novel method and a new framework for intention-based decision making. It demonstrates how recognizing others' intentions can enhance decision-making processes and, through computational models employing evolutionary game theory, shows that this ability promotes cooperation among self-regarding agents. Furthermore, the work explores how commitment facilitates the evolution of cooperation and amplifies the effectiveness of intention recognition, leading to a combined strategy that further improves cooperative outcomes.

This work is presented as a unique and timely monograph that offers a self-contained exploration of intention recognition and commitment in the context of cooperative behavior evolution. The book's approach integrates artificial intelligence techniques with evolutionary game theory models to demonstrate its core arguments. The author's detailed analysis and novel proposals are intended to provide readers with a comprehensive understanding of these cognitive abilities' impact on cooperation. The structured presentation aims to guide readers through complex computational modeling and theoretical frameworks.