The roles of associational and causal reasoning in problem solving
Artificial Intelligence
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
An algorithm for probabilistic planning
Artificial Intelligence - Special volume on planning and scheduling
An autonomous spacecraft agent prototype
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Map learning and high-speed navigation in RHINO
Artificial intelligence and mobile robots
Structured reactive controllers: controlling robots that perform everyday activity
Proceedings of the third annual conference on Autonomous Agents
A Computer Model of Skill Acquisition
A Computer Model of Skill Acquisition
Fast Probabilistic Plan Debugging
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Using Simulation-Based Projection to Plan in an Uncertain and Temporally Complex World
Using Simulation-Based Projection to Plan in an Uncertain and Temporally Complex World
Development of iterative real-time scheduler to planner feedback
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Managing plans: Integrating deliberation and reactive execution schemes
Robotics and Autonomous Systems
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Acting efficiently and meeting deadlines requires autonomous robots to schedule their activities. It also requires them to act flexibly: to exploit opportunities and avoid problems as they occur. Scheduling activities to meet these requirements is an important research problem in its own right. In addition, it provides us with a problem domain where modern symbolic AI planning techniques could considerably improve the robots' behavior. This paper describes ppsd, a novel planning technique that enables autonomous robots to impose order constraints on concurrent percept-driven plans to increase the plans' efficiency. The basic idea is to generate a schedule under simplified conditions and then to iteratively detect, diagnose, and eliminate behavior flaws caused by the schedule based on a small number of randomly sampled symbolic execution scenarios. The paper discusses the integration of ppsd into the controller of an autonomous robot office courier and gives an example of its use.