Thisbook mainly aims at solving the problems in both cooperative and competitivemulti-agent systems (MASs), exploring aspects such as how agents caneffectively learn to achieve the shared optimal solution based on their localinformation and how they can learn to increase their individual utility byexploiting the weakness of their opponents. The book describes fundamental andadvanced techniques of how multi-agent systems can be engineered towards thegoal of ensuring fairness, social optimality, and individual rationality; awide range of further relevant topics are also covered both theoretically andexperimentally. The book will be beneficial to researchers in the fields ofmulti-agent systems, game theory and artificial intelligence in general, as wellas practitioners developing practical multi-agent systems.
