Distribution over Beliefs for Memory Bounded Dec-POMDP Planning
  We propose a new point-based method for approximate planning in Dec-POMDP
which outperforms the state-of-the-art approaches in terms of solution quality.
It uses a heuristic estimation of the prior probability of beliefs to choose a
bounded number of policy trees: this choice is formulated as a combinatorial
optimisation problem minimising the error induced by pruning.
