Search Constraints

Start Over
Filtering by: Creator Munts, Steven R. Remove constraint Creator: Munts, Steven R. Degree Level Doctoral Remove constraint Degree Level: Doctoral Subject Markov processes Remove constraint Subject: Markov processes

Search Results

  • A hazardous-inspection model with costly repair

    Creator:
    Yang, Minghui
    Abstract:
    An inspection-repair model is developed that presumes inspection is hazardous to the system being inspected. The form of the optimal inspection-repair policy is determined for different ranges of the model's parameters. The model is formulated as a partially observable Markov decision process with finite numbers of states and actions. The...
    Resource Type:
    Dissertation
    Full Text:
    dissertation, and to Dr. Steven J. Knapp, who has supported me for almost two years and who has given me a lot

  • 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
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 4.6 Plots of V UCB(λ ν lower) R , VR − V UCB(λνlower) R , and V UCB(λνlower) C on the vertical

  • 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
    Full Text:
    current program location `′ is at choice (A′, a′). The last choice is (A, a) with reward r seen in

  • 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
    Full Text:
    problems under uncertainty. An MDP is a tuple (S,A, T,R, γ) where S is a finite state-space, A is a finite