A Game Theoretic Approach to Multi-Agent Cooperation with Application to Economic Systems

Consensus problem with multi-agent systems has interested researchers in various areas. Its difficulties tend to appear when available information of each agent is limited for achieving consensus. Besides, it is not always the case that agents can catch the whole states of the others; an output is often the only possible measurement for each agent in applications. The idea of graph Laplacian is then of help to address such a troublesome situation. While every single agent obviously makes decision to achieve an individual goal of minimizing its own cost functional, all agents as a team can obtain even more improvement by cooperation in some cases, which leads to cooperative game theoretic approach. The main goal of this master thesis is to accomplish a combination of optimal control theory and cooperative game theory in order to solve the output consensus problem with limited network connectivity. Along with this combination, bargaining problems are considered out of necessity.