Partially Observable Markov Decision Processes (POMDPs) provide an appropriately rich model for agents operating under partial knowledge of the environment. Since finding an opti...
Yan Virin, Guy Shani, Solomon Eyal Shimony, Ronen ...
Finding all satisfying assignments of a propositional formula has many applications in the design of hardware and software. An approach to this problem augments a clause-recording...
Oversubscribed scheduling problems require removing or partially satisfying tasks when enough resources are not available. For a particular oversubscribed problem, Air Force Satel...
Laura Barbulescu, L. Darrell Whitley, Adele E. How...
Most formulations of Reinforcement Learning depend on a single reinforcement reward value to guide the search for the optimal policy solution. If observation of this reward is rar...
Generalized belief propagation (GBP) has proven to be a promising technique for approximate inference tasks in AI and machine learning. However, the choice of a good set of cluste...