We explore an extension of nonatomic routing games that we call Markov decision process routing games where each agent chooses a transition policy between nodes in a network rather than a path from an origin node to a destination node, i.e. each agent in the population solves a Markov decision process rather than a shortest path problem. We define the appropriate version of a Wardrop equilibrium as well as a potential function for this game in the finite horizon (total reward) case. Thiswork can be thought of as a routinggame-based formulation of continuous population stochastic games (mean-field games or anonymous sequential games). We apply our model to the problem of ridesharing drivers competing for customers.
CITATION STYLE
Calderone, D., & Sastry, S. S. (2017). Markov decision process routing games. In Proceedings - 2017 ACM/IEEE 8th International Conference on Cyber-Physical Systems, ICCPS 2017 (part of CPS Week) (pp. 273–279). Association for Computing Machinery, Inc. https://doi.org/10.1145/3055004.3055026
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