Symmetry in Markov Decision Processes and its Implications for Single Agent and Multiagent Learning

@inproceedings{Zinkevich2001SymmetryIM,
  title={Symmetry in Markov Decision Processes and its Implications for Single Agent and Multiagent Learning},
  author={Martin Zinkevich and Tucker R. Balch},
  booktitle={ICML},
  year={2001}
}
This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in single agent systems as well as multiagent systems and multirobot systems. We prove that if an MDP possesses a symmetry, then the optimal value function andQ function are similarly… CONTINUE READING

Topics

Statistics

051015201620172018
Citations per Year

Citation Velocity: 5

Averaging 5 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.