Towards Comprehensive Computational Models for Plan-Based Control of Autonomous Robots

In this paper we present an overview of recent developments in the plan-based control of autonomous robots. We identify computational principles that enable autonomous robots to accomplish complex, diverse, and dynamically changing tasks in challenging environments. These principles include plan-based high-level control, probabilistic reasoning, plan transformation, and context and resource-adaptive reasoning. We will argue that the development of comprehensive and integrated computational models of plan-based control requires us to consider different aspects of plan-based control — plan representation, reasoning, execution, and learning — together and not in isolation. This integrated approach enables us to exploit synergies between the different aspects and thereby come up with simpler and more powerful computa-