Markov decision process routing games

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 proce...

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Vydané v:2017 ACM IEEE 8th International Conference on Cyber Physical Systems (ICCPS) s. 273 - 279
Hlavní autori: Calderone, Dan, Sastry, S. Shankar
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: New York, NY, USA ACM 18.04.2017
Edícia:ACM Other Conferences
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ISBN:9781450349659, 145034965X
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Shrnutí: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. This work can be thought of as a routing-game-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.
ISBN:9781450349659
145034965X
DOI:10.1145/3055004.3055026