Planning under uncertainty for real-world multiagent systems

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• Dr. Matthijs Spaan, Intelligent Robot and Systems Group, Institute for Systems and Robotics, Instituto Superior Técnico, Lisbon
• Monday 11 April 2011, 16:00-17:00
• UG40, School of Computer Science.

If you have a question about this talk, please contact Leandro Minku.

As distributed intelligent systems are becoming more ubiquitous in society, the need for intelligent decision making in multiagent systems grows. The decision-making problem is particularly challenging when uncertainty is involved, and has not yet been solved satisfactorily. In this talk I will give an overview of our recent work, which targets planning in real-world multiagent systems.

For an agent in isolation, planning under uncertainty has been studied using decision-theoretic models like Partially Observable Markov Decision Processes (POMDPs). I will discuss how we use POMD Ps for problems involving active cooperative perception, in which a mobile robot interacts with a network of surveillance cameras. In the multiagent case, related models such as Decentralized POMD Ps have been gaining popularity. I will present recent algorithmic advances in optimal Dec-POMDP solving, as well as techniques for exploiting local interactions between agents. Finally, I will detail how multiagent planning under uncertainty can be applied to networks of robots and sensors.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

This talk is included in these lists:

• Artificial Intelligence and Natural Computation seminars
• Computer Science Departmental Series
• Computer Science Distinguished Seminars
• UG40, School of Computer Science
• computer sience

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