Reinforcement learning addresses the dilemma between exploration to find profitable actions and exploitation to act according to the best observations already made. Bandit proble...
— We present a novel approach for determining robot movements that efficiently accomplish the robot’s tasks while not hindering the movements of people within the environment....
Brian Ziebart, Nathan D. Ratliff, Garratt Gallaghe...
As the amount of multimodal meetings data being recorded increases, so does the need for sophisticated mechanisms for accessing this data. This process is complicated by the diffe...
Abstract. The Grid Modeling and Simulation (GridSim) toolkit provides a comprehensive facility for simulation of application scheduling in different Grid computing environments. H...
The Constraint-Based Agent (CBA) framework is a set of tools for designing, simulating, building, verifying, optimizing, learning and debugging controllers for agents embedded in a...