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Abstract
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| We extend previous works on stochastic dynamic potential games (DPGs) with constrained continuous state-action spaces, and present a closed-loop analysis when the players are forced to use parametric policies. Our main assumption is that the parameter space must be finite-dimensional. We show that a closed-loop Nash equilibrium of a DPG can be found by solving a related optimal control problem (OCP). This is convenient since solving a single OCP (which is a single-objective problem) is usually much simpler than solving the original set of coupled OCPs that form the game (which is a multiobjective problem). | |
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International
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Si |
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Congress
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Learning, Inference and Control of Multi-Agent Systems Workshop on Neural Information Processing (NIPS) |
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970 |
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Place
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Barcelona |
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Reviewers
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Si |
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ISBN/ISSN
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Start Date
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10/12/2016 |
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End Date
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10/12/2016 |
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From page
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1 |
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To page
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6 |
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