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.
