Strategic Interactions in Multiagent Systems

点击翻译按钮获取中文摘要

Self-interested, or competitive, multiagent systems are settings where multiple agents interact while potentially having different goals and information. Some of the key issues in these systems are i) how and when should agents coordinate their actions and decisions and ii) how to design protocols to handle the agents' self-interest and achieve system-wide desirable goals. Examples of self-interested multiagent systems abound, ranging from voting to game-playing, and ideas from the multiagent systems research community have had significant impact in applications ranging from port security to the Smart Grid. In many multiagent systems the interactions of the agents are constrained in some way. For example, the underlying social network may encourage and support certain interactions over others, or the transportation network may facilitate resource exchange between certain agents while forming a barrier between others. Thus, when studying and discussing strategic behaviour it is important to account for and understand how the underlying constraints affect the decisions and actions of the agents and how this leads to different outcomes. I will investigate multiagent systems where the constraints on agents' interactions can be explicitly modelled by a graph or network. I call such multiagent systems "networked multiagent systems" or "networked MAS" for short. I will develop appropriate models for these systems and investigate the game-theoretic and computational issues that arise. The significance of the work lies in deepening our understanding of how self-interested agents should organize and coordinate their actions, a key research problem in multiagent systems and artificial intelligence. Results from this research will also lead to novel applications in areas such as electronic commerce, social networks and the Smart Grid.