Complex adaptive systems (cas) is proposed by John Holland and it is defined as systems that involve many components that adapt or learn as they interact. Adaptation builds complexity. Cas is the core problems of Complex Systems research, such as the origin of life, evolution of species, organ development, learning mechanisms of the brain, sustainable development of ecosystems, market evolution, the origin of language, etc.

In a cas, agents are co-adapting to each other through interactions. There are very few theories about co-adaption and co-evolution. Game is a typical example to study co-adaption because it has the prominent nature of co-evolution: two players learn and adjust their strategies through game playing. The study of how players co-evolve in games will shed light on co-adaptation in cas.

This project explores several key issues of CAS by case study based on dynamic games: by using examples such as combinatorial games and other classical games, we study the law of how two players adapt to each other through playing game, the characteristics of dynamics of co-evolution, the condition for implementing “arm race” phenomenon, the role of information of the opponent in games, as well as how we use soft-control to intervene into CAS ( for example, to induce group cooperation based on direct / indirect reciprocity models).