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Filtering by: Subject Decision making -- Mathematical models Remove constraint Subject: Decision making -- Mathematical models

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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
Adiabatic Markov Decision Process : convergence of value iteration algorithm

Creator:

Duong, Thai

Abstract:

Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not...

Resource Type:

Masters Thesis
Just enough die-level functional test : optimizing IC test via machine learning and decision theory

Creator:

Fountain, Tony R.

Abstract:

This research explores the hypothesis that methods from decision theory and machine learning can be combined to provide practical solutions to current manufacturing control problems. This hypothesis is explored by developing an integrated approach to solving one manufacturing problem - the optimization of die-level functional test. An integrated circuit (IC)...

Resource Type:

Dissertation
A mathematical modeling framework for scheduling and managing multiple concurrent tasks

Creator:

Shakeri, Shakib

Abstract:

Occurrence of human error in highly complex systems, such as a cockpit, can be disastrous and/or overwhelmingly costly. Mismanagement of multiple concurrent tasks has been observed by researchers to be a type of repetitive human error in previous studies of accidents and incidents. This error may occur in the form...

Resource Type:

Dissertation
Effective decision-theoretic assistance through relational hierarchical models

Creator:

Natarajan, Sriraam

Abstract:

Building intelligent computer assistants has been a long-cherished goal of AI. Many intelligent assistant systems were built and fine-tuned to specific application domains. In this work, we develop a general model of assistance that combines three powerful ideas: decision theory, hierarchical task models and probabilistic relational languages. We use the...

Resource Type:

Dissertation

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Academic Affiliation

Electrical Engineering and Computer Science3
Computer Science1
Industrial and Manufacturing Engineering1

Advisor

Tadepalli, Prasad2
Dietterich, Thomas G.1
Logendran, Rasaratnam1
Nguyen, Thinh P.1

Commencement Year

Commencement Year range begin – Commencement Year range end

Current results range from 1999 to 2017

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Committee Member

Fern, Alan2
Bose, Bella1
Dietterich, Thomas1
Emerson, Sarah1
Fern, Xiaoli1
more Committee Members »

Creator

Duong, Thai1
Fountain, Tony R.1
Natarajan, Sriraam1
Raghavan, Aswin1
Shakeri, Shakib1

Date

Date range begin – Date range end

Current results range from 1998 to 2017

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Decade

2010-20192
2000-20092
1990-19991

Degree Field

Computer Science3
Electrical and Computer Engineering1
Industrial Engineering1

Degree Level

Doctoral4
Master's1

Degree Name

Doctor of Philosophy (Ph.D.)4
Master of Science (M.S.)1

File Format

application/pdf1

Language

English [eng]5

License

All rights reserved4

Non-Academic Affiliation

Oregon State University. Graduate School5

Peer Reviewed

No5

Resource Type

Dissertation4
Masters Thesis1

Rights Statement

In Copyright4
Copyright Not Evaluated1

Subject

Decision making -- Mathematical models[remove]5
Markov processes2
Statistical decision2
Artificial intelligence1
Constrained optimization1
more Subjects »

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