We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
— Despite major advances within the affective computing research field, modelling, analysing, interpreting and responding to naturalistic human affective behaviour still remains...
Abstract— This paper presents the Discrete Search Leading continuous eXploration (DSLX) planner, a multi-resolution approach to motion planning that is suitable for challenging p...
This paper presents a new method called Transition-based RRT (T-RRT) for path planning problems in continuous cost spaces. It combines the exploration strength of the RRT algorith...