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Filtering by: Creator Boutilier, Jordan Subject Markov processes

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
Simulator-Defined MDP Planning with Applications in Natural Resource Management

Creator:

Alkaee Taleghan, Majid

Abstract:

This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...

Resource Type:

Dissertation
Incorporating and Learning Behavior Constraints for Sequential Decision Making

Creator:

Pinto, Jervis

Abstract:

Writing a program that performs well in a complex environment is a challenging task. In such problems, a method of deterministic programming combined with reinforcement learning (RL) can be helpful. However, current systems either force developers to encode knowledge in very specific forms (e.g., state-action features), or assume advanced RL...

Resource Type:

Dissertation