Abstract. We consider a control problem where the decision maker interacts with a standard Markov decision process with the exception that the reward functions vary arbitrarily ove...
We present an efficient generalization of the sparse pseudo-input Gaussian process (SPGP) model developed by Snelson and Ghahramani [1], applying it to binary classification pro...
Summarizing large multidimensional datasets is a challenging task, often requiring extensive investigation by a user to identify overall trends and important exceptions to them. W...
We describe HDL, an algorithm that learns HTN domain descriptions by examining plan traces produced by an expert problem-solver. Prior work on learning HTN methods requires that a...
Most experiments in research on autonomous agents and mobile robots are performed either in simulation or on robots with static physical properties; evolvable hardware is hardly e...