ABSTRACT
Multi-Agent Agreement Problems (MAP) - the ability of a population of agents to search out and converge on a common state - are central issues in many multi-agent settings, from distributed sensor networks, to meeting scheduling, to development of norms, conventions, and language. While much work has been done on particular agreement problems no unifying framework exists for comparing MAPs that vary in, e.g., strategy space complexity, inter-agent accessibility, and solution type, and understanding their relative complexities. We present such a unification, the Distributed Optimal Agreement (DOA) framework, and show how it captures a wide variety of agreement problems. To demonstrate DOA and its power we apply it to convention evolution. 1
- F. Cucker, S. Smale, and D.-X. Zhou. Modeling language evolution. Foundations of Computational Mathematics, 4(3):315--343, July 2004. Google ScholarDigital Library
- K. Lakkaraju and L. Gasser. The complexity of finding an optimal policy for language convergence. In Proceedings of the the Ninth International Conference on the SIMULATION OF ADAPTIVE BEHAVIOR (SAB'06), 2006. Google ScholarDigital Library
- K. Lakkaraju and L. Gasser. A unified framework for multi-agent agreement. Technical Report UILU-ENG-2006-1843, University of Illinois, Urbana-Champaign, 2007.Google ScholarDigital Library
- N. A. Lynch. Distributed Algorithms. Morgan Kaufmann, 1997. Google ScholarDigital Library
- F. A. Matsen and M. A. Nowak. Win-stay, lose-shift in language learning from peers. PNAS, 101(52):18053--18057, December 2004.Google ScholarCross Ref
- M. A. Nowak, N. L. Komarova, and P. Niyogi. Computational and evolutionary aspects of language. Nature, 417(6889):611--617, June 2002.Google ScholarCross Ref
- Y. Shoham and M. Tennenholtz. On the emergence of social conventions: modeling, analysis, and simulations. Artificial Intelligence, 94(1--2):139--166, July 1997. Google ScholarDigital Library
- L. Steels. The origins of ontologies and communication conventions in multi-agent systems. Autonomous Agents and Multi-Agent Systems, 1(2):169--194, October 1998. Google ScholarDigital Library
- K. Wagner, J. Reggia, J. Uriagereka, and G. Wilkinson. Progress in the simulation of emergent communication and language. Adaptive Behavior, 11:37--69, 2003.Google ScholarCross Ref
Index Terms
- A unified framework for multi-agent agreement
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