Envelope-based Planning in Relational MDPs

摘要

Introduction: A mobile robot acting in the world is faced with a large amount of sensory data and uncertainty in its action outcomes. Indeed, almost all interesting sequential decision-making domains involve large state spaces and large, stochastic action sets. We investigate a way to act intelligently as quickly as possible in domains where finding a complete policy would take a hopelessly long time. This approach, Relational Envelope-based Planning (REBP) [4] tackles large, noisy problems along two