Compositional Planning Using Optimal Option Models

Understand

In this paper we introduce a framework for option model composition.

• Option models are temporal abstractions that, like macro-operators in classical planning, jump directly from a start state to an end state.
• Prior work has focused on constructing option models from primitive actions, by intra-option model learning; or on using option models to construct a value function, by inter-option planning.
• We present a unified view of intra- and inter-option model learning, based on a major generalisation of the Bellman equation.