Game theory is rapidly gaining traction in several engineering applications as the natural framework for multi-agent decision making. Yet, unlike optimization, game theory has no mature, general-purpose solvers. Computing an equilibrium of a multi-agent noncooperative game amounts to solving a large-scale generalized equation, and available solutions rely on restrictive assumptions, offer no control over which equilibrium is returned, and scale poorly with the size of the problem. This position addresses the computational side of this gap.
We are seeking a highly motivated postdoctoral researcher with a solid background in one or more of the following areas: game theory, optimization algorithms, and numerical methods. The successful candidate will develop efficient algorithms and computational tools for equilibrium computation in multi-agent games. The work will focus on:
- Scalable algorithms for various equilibrium problems in multi-agent games;
- Open-source computational tools and benchmarks;
- Application of game-theoretic solvers to multi-agent autonomous systems
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