We describe how a physical robot can learn about objects from its own autonomous experience in the continuous world. The robot identifies statistical regularities that allow it t...
We contribute an approach for interactive policy learning through expert demonstration that allows an agent to actively request and effectively represent demonstration examples. I...
This paper proposes an emotion model for life-like agents with emotions and motivations. This model consists of reactive and deliberative mechanisms. The former generates low-leve...
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
This paper investigates the problem of improving the performance of general state-of-the-art robot control systems by autonomously adapting them to specific tasks and environments...