Houjun Liu


Main problem: joint actions and observations are exponential by the number of agents.

Solution: Smaple-based online planning for multiagent systems. We do this with the factored-value POMCP.

  • factored statistics: reduces the number of joint actions (through action selection statistics)
  • factored trees: reduces the number of histories

Multiagent Definition

  • \(I\) set of agents
  • \(S\) set of states
  • \(A_{i}\) set of states for each agent \(i\)
  • \(T\) state transitions
  • \(R\) reward function
  • \(Z_{i}\) joint observations for each agents
  • \(O\) set of observations

Coordination Graphs

you can use sum-product elimination to shorten the Baysian Network of the agent Coordination Graphs (which is how agents influnece each other).

Mixture of Experts

Directly search for the best joint actions; computed by MLE of the total value.