Skills & Symbols

Here we focus on learning abstract representations, which we believe are an important component if we are ever to apply reinforcement learning to the real world. In particular, we focus on skill- and symbol-discovery, as well as the interplay between the two. We have applied our approaches to challenging pixel-based tasks that require high-level planning, and have shown that symbolic representations can be learned directly from low-level sensor data.