Scalable Multiagent Planning Using Probabilistic Inference

@inproceedings{Kumar2011ScalableMP,
  title={Scalable Multiagent Planning Using Probabilistic Inference},
  author={Akshat Kumar and Shlomo Zilberstein and Marc Toussaint},
  booktitle={IJCAI},
  year={2011}
}
Multiagent planning has seen much progress with the development of formal models such as DecPOMDPs. However, the complexity of these models—NEXP-Complete even for two agents— has limited scalability. We identify certain mild conditions that are sufficient to make multiagent planning amenable to a scalable approximation w.r.t. the number of agents. This is achieved by constructing a graphical model in which likelihood maximization is equivalent to plan optimization. Using the Expectation… CONTINUE READING
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References

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Showing 1-10 of 18 references

In ICAPS

  • Stefan J. Witwicki, Edmund H. Durfee. Influence-based policy abstraction for Dec-POMDPs
  • pages 185–192,
  • 2010
Highly Influential
6 Excerpts

Mor

  • Daniel S. Bernstein, Roie Givan, Neil Immerman, Shlomo Zilberstein. The complexity of decentralized contr processes
  • 27:819–840,
  • 2002
Highly Influential
15 Excerpts

In UAI

  • Akshat Kumar, Shlomo Zilberstein. Anytime planning for decentralized PO maximization
  • pages 294–301,
  • 2010

Jaamas

  • Christopher Amato, Daniel S. Bernstein, Shlomo Zilberstein. Optimizing fixed-size stochastic cont POMDPs, decentralized POMDPs
  • 21(3):293– 320,
  • 2010
1 Excerpt

Event-detecting multi-agent MDPs: complexity and constant-factor approximation

  • Akshat Kumar, Shlomo Zilberstein
  • IJCAI, pages 201–207,
  • 2009
1 Excerpt

In ICML

  • Marc Toussaint, Amos J. Storkey. Probabilistic inference for solving discrete, continuous state Markov decision processes
  • pages 945–952,
  • 2006
3 Excerpts

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