In this meeting of the AI Seminar Series, Dr. Christian Muise will talk about using fully observable non-deterministic planning to compute contingent plans.

Title: Computing Contingent Plans via Fully Observable Non-Deterministic Planning

Speaker:Dr. Christian Muise

When: Tuesday, 5th August 11 AM - 12 NOON

Where: Doug McDonnell-10.05

Abstract:
Planning with sensing actions under partial observability is a computationally challenging problem that is fundamental to the realization of AI tasks in areas as diverse as robotics, game playing, and diagnostic problem solving. Recent work on generating plans for partially observable domains has advocated for online planning, claiming that offline plans are often too large to generate. Here we push the envelope on this challenging problem, proposing a technique for generating conditional (aka contingent) plans offline. The key to our plannerís success is the reliance on state-of-the-art techniques for fully observable non-deterministic (FOND) planning. In particular, we use an existing compilation for converting a planning problem under partial observability and sensing to a FOND planning problem. With a modified FOND planner in hand, we are able to scale beyond previous techniques for generating conditional plans with solutions that are orders of magnitude smaller than previously possible in some domains.

Bio:
Dr. Christian Muise completed his Ph.D.degree at the University of Toronto in 2013. He is currently a Research Fellow in the Computing and Information Systems Department at the University of Melbourne.

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