Planning with Incomplete Information for Robot Problems
Papers from the AAAI Spring Symposium
As the planning and robotics communities have begun addressing more complex, real-world problems, it has become apparent that planners usually do not have complete information about all aspects of a target domain. Incomplete information comes in many forms, including incomplete information about the initial conditions, the effects of actions, the discerning power of perceptual systems, etc.
This symposium brings together the robotics and planning communities to focus on the common challenge of constructing systems that plan and act robustly in spite of incomplete information. Current relevant work includes reasoning with uncertainty, interleaving planning and execution, conditional nonlinear planning, deferred planning, etc. The symposium is designed with two goals in mind, one ground-level goal and one meta goal that also serves as a reference point for future discussions:
- Present and discuss successful solution techniques for specific types of incomplete information.
- Construct a taxonomy of the types of incomplete information faced by real-world systems and address underlying definitional questions; e.g., how do we define "completeness" for interleaving systems?