Bayesian A* Tree Search with Expected O(N) Node Expansions: Applications to Road Tracking

Many perception, reasoning, and learning problems can be expressed as Bayesian inference. We point out that formulating a problem as Bayesian inference implies specifying a probability distribution on the ensemble of problem instances. This ensemble can be used for analyzing the expected complexity of algorithms and also the algorithm-independent limits of inference. We illustrate this problem by analyzing the complexity of tree search. In particular, we study 1 

• Type: Journal
• Year: 2002
• Where: NECO
• Authors: James M. Coughlan, Alan L. Yuille
• Keywords: Bayesian Inference, Many Perception, NECO 2002, Probability Distribution