A reinforcement learning scheme for the equilibrium of the in-vehicle route choice problem based on congestion game.
Bo ZhouQiankun SongZhenjiang ZhaoTangzhi LiuPublished in: Appl. Math. Comput. (2020)
Keyphrases
- learning scheme
- traffic congestion
- nash equilibrium
- game theory
- nash equilibria
- travel time
- games with incomplete information
- pure strategy
- learning algorithm
- traffic information
- game theoretic
- road network
- equilibrium point
- repeated games
- traffic flow
- congestion games
- reinforcement learning
- packet transmission
- fictitious play
- incomplete information
- extensive form games
- subgame perfect equilibrium
- stochastic games
- computer games
- pick up and delivery
- mixed strategy
- traffic conditions
- shortest path
- equilibrium strategies
- video games
- urban areas
- traffic data
- game playing
- traffic light
- correlated equilibrium
- imperfect information
- perfect information
- rule learning
- moving objects