IJCAI-2011 Tutorial

Advanced Introduction to Planning: Models and Methods

Hector Geffner

ICREA & Universitat Pompeu Fabra
Barcelona, Spain

Planning is the model-based approach to autonomous behavior where the agent behavior is derived automatically from a model. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are intractable in the worst case. In this tutorial, we will look at the variety of models used in AI planning, and the techniques that have been developed for solving them. The goal is to provide a modern and coherent view of planning that is comprehensive but not shallow. The target audience of this tutorial is students and researchers interested in autonomous behavior and cognitive science.


Introduction to AI Planning
Classical Planning as Heuristic Search
Beyond Classical Planning: Transformations: Soft goals, Incomplete Info, Plan Recognition
Planning with Uncertainty: Markov Decision Processes (MDPs)
Planning with Incomplete Information: Partially Observable MDPs (POMDPs)
Open Problems and Challenges