Strategies in multi-agent systems: From implicit to implementable
01 / 2009 - 01 / 2013
Modelling intelligent and rational interaction in multi-agent systems has been one of the main issues in Artificial Intelligence that gained momentum in the last decade of the past century. The 'agents' under discussion mainly refer to autonomous actors like software programs, robots and even humans. Interaction among them can be cooperative as well as non-cooperative. This is now merging into broader studies of formal models of society, where computer science meets decision theory, game theory, and social choice theory, for instance in the study of rational deliberation and decision making. A term used for this connection is 'social software', an interesting perspective, but as yet without a complete theory . There are many detailed studies of agents' knowledge, beliefs, preferences, and also of their long-term powers for influencing the outcomes of games. But we do not have a good theory of what may be the most crucial ingredient here: the plans or strategies that information-processing agents have for achieving their goals, in other words, their 'know-how' in addition to their 'know-that'. This is the main topic of this research project. The expected results of the proposed research are as follows: -Sophisticated logical theories of strategies, influenced by the epistemic states of the agents in a dynamic setting. -Associated programming language to model strategy choices in interaction. -Computational models of strategies in multi-agent interaction systems so as to capture the complex ways of human interaction. -User-friendly software to model real-life interactive systems.