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John Baras
University of Maryland
Title: Collaboration in Networks of Autonomous Agents: Coalitional Games, Constraints and Architectures
Abstract: In this talk we develop a unifying analytical and optimization framework for the design, operation and performance evaluation of networks of autonomous agents. The fundamental view is that agents in such a network are dynamic entities that collaborate because via collaboration they can accomplish objectives and goals much better than working alone, or even accomplish objectives that they cannot achieve alone at all. Yet the benefits derived from such collaboration require some costs (or expenditures), for example due to communications. Or in equivalent terms, the collaboration is subject to constraints (static and dynamic). Understanding and quantifying this tradeoff between the benefits vs the costs of collaboration, leads to new methods that can be used to analyze, design and control/operate networks of agents. Multiple metrics for benefits and costs can be considered within this framework. An important, yet not emphasized todate, aspect of collaboration is the role of topologies and connectivities linking the agents. We demonstrate that connectivities related to small world graphs and expander graphs offer dramatic advantages with respect to many problems that need to be solved in a distributed manner in collaborative control and communication. These topologies are efficient from the perspective of costs yet lead to fast convergence of distributed algorithms from the benefits perspective. We show how they can be self-generated in response to cost-benefit tradeoffs. We illustrate by simple examples.