Abstract
The response to a large-scale disaster, e.g. an earthquake or a terrorist incident, urges for low-cost policies that coordinate sequential decisions of multiple agents. Decisions range from collective (common good) to individual (self-interested) perspectives, intuitively shaping a two-layer decision model. However, current decision theoretic models are either purely collective or purely individual and seek optimal policies. We present a two-layer, collective versus individual (CvI) decision model and explore the tradeoff between cost reduction and loss of optimality while learning coordination skills. Experiments, in a partially observable domain, test our approach for learning a collective policy and results show near-optimal policies that exhibit coordinated behavior.
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Trigo, P., Jonsson, A., Coelho, H. (2006). Coordination with Collective and Individual Decisions. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds) Advances in Artificial Intelligence - IBERAMIA-SBIA 2006. IBERAMIA SBIA 2006 2006. Lecture Notes in Computer Science(), vol 4140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11874850_8
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DOI: https://doi.org/10.1007/11874850_8
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