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Filtering by: Creator Boutilier, Jordan Committee Member Fern, Xiaoli

Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

Creator:

Raghavan, Aswin

Abstract:

Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...

Resource Type:

Dissertation
New learning modes for sequential decision making

Creator:

Judah, Kshitij

Abstract:

This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy learning algorithms o er teachers little flexibility in how policies are taught. In particular, one of two learning modes is typically considered: 1)...

Resource Type:

Dissertation