In dialogue systems, it is necessary to decode the user input into semantically meaningful units. These semantical units, usually Dialogue Acts (DA), are used by the system to pro...
Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have a...
We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
— Matching laser range scans observed at different points in time is a crucial component of many robotics tasks, including mobile robot localization and mapping. While existing t...