We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Distributed Partially Observable Markov Decision Problems (POMDPs) are emerging as a popular approach for modeling multiagent teamwork where a group of agents work together to joi...
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
In model-based control, a planner uses a system description to create a plan that achieves production goals. The same model can be used by model-based diagnosis to indirectly infe...
Lukas Kuhn, Bob Price, Minh Binh Do, Juan Liu, Ron...
Many applications of networks of agents, including mobile sensor networks, unmanned air vehicles, autonomous underwater vehicles, involve 100s of agents acting collaboratively und...
Janusz Marecki, Tapana Gupta, Pradeep Varakantham,...