Principled Option Learning in Markov Decision Processes

Understand

It is well known that options can make planning more efficient, among their many benefits.

• Thus far, algorithms for autonomously discovering a set of useful options were heuristic.
• Naturally, a principled way of finding a set of useful options may be more promising and insightful.
• In this paper we suggest a mathematical characterization of good sets of options using tools from information theory.