State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...
In this paper, we study multiple target detection using Bayesian learning. The main aim of the paper is to present a computationally efficient way to compute the belief map update ...
When exploring a game over a large strategy space, it may not be feasible or cost-effective to evaluate the payoff of every relevant strategy profile. For example, determining a p...
Patrick R. Jordan, Yevgeniy Vorobeychik, Michael P...