Delayed reward-based genetic algorithms for partially observable Markov decision problems

Yoshihide Yamashiro; Atsushi Ueno; Hideaki Takeda

doi:10.1002/scj.10230

Delayed reward-based genetic algorithms for partially observable Markov decision problems

Systems and Computers in Japan ◽

10.1002/scj.10230 ◽

2004 ◽

Vol 35 (2) ◽

pp. 66-78 ◽

Cited By ~ 2

Author(s):

Yoshihide Yamashiro ◽

Atsushi Ueno ◽

Hideaki Takeda

Keyword(s):

Genetic Algorithms ◽

Decision Problems ◽

Markov Decision Problems ◽

Delayed Reward ◽

Markov Decision ◽

Partially Observable Markov ◽

Partially Observable

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A superharmonic approach to solving infinite horizon partially observable Markov decision problems

Mathematical Methods of Operations Research ◽

10.1007/bf01415066 ◽

1995 ◽

Vol 41 (1) ◽

pp. 71-88 ◽

Cited By ~ 2

Author(s):

D. J. White

Keyword(s):

Infinite Horizon ◽

Decision Problems ◽

Markov Decision Problems ◽

Markov Decision ◽

Partially Observable Markov ◽

Partially Observable

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Dynamic Risk Measures for Finite-State Partially Observable Markov Decision Problems

2015 Proceedings of the Conference on Control and its Applications ◽

10.1137/1.9781611974072.22 ◽

2015 ◽

pp. 153-158

Author(s):

Jingnan Fan ◽

Andrzej Ruszczyński

Keyword(s):

Risk Measures ◽

Decision Problems ◽

Dynamic Risk Measures ◽

Dynamic Risk ◽

Markov Decision Problems ◽

Finite State ◽

Markov Decision ◽

Partially Observable Markov ◽

Partially Observable

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FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems

International Journal of Advanced Robotic Systems ◽

10.5772/5817 ◽

2004 ◽

Vol 1 (4) ◽

pp. 27

Author(s):

Toygar Karadeniz ◽

Levent Akin

Keyword(s):

Decision Problems ◽

Fuzzy Approach ◽

Q Learning ◽

Markov Decision Problems ◽

Neuro Fuzzy ◽

Markov Decision ◽

Partially Observable Markov ◽

Partially Observable

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Partially Observable Markov Decision Problems in Finance

Universitext - Markov Decision Processes with Applications to Finance ◽

10.1007/978-3-642-18324-9_6 ◽

2011 ◽

pp. 175-189

Author(s):

Nicole Bäuerle ◽

Ulrich Rieder

Keyword(s):

Decision Problems ◽

Markov Decision Problems ◽

Markov Decision ◽

Partially Observable Markov ◽

Partially Observable

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Representing and Solving Air Campaign Problems as Partially Observable Markov Decision Problems

10.21236/ada388558 ◽

2001 ◽

Author(s):

Thomas L. Dean

Keyword(s):

Decision Problems ◽

Markov Decision Problems ◽

Markov Decision ◽

Partially Observable Markov ◽

Partially Observable

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Model Acquisition for Markov Decision Problems

10.21236/ada373795 ◽

1998 ◽

Author(s):

Thomas L. Dean

Keyword(s):

Decision Problems ◽

Model Acquisition ◽

Markov Decision Problems ◽

Markov Decision

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Model Acquisition for Markov Decision Problems

10.21236/ada380049 ◽

1998 ◽

Author(s):

Thomas Dean

Keyword(s):

Decision Problems ◽

Model Acquisition ◽

Markov Decision Problems ◽

Markov Decision

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Solving Uncertain Markov Decision Problems: An Interval-Based Method

Lecture Notes in Computer Science - Advances in Natural Computation ◽

10.1007/11881223_120 ◽

2006 ◽

pp. 948-957 ◽

Cited By ~ 2

Author(s):

Shulin Cui ◽

Jigui Sun ◽

Minghao Yin ◽

Shuai Lu

Keyword(s):

Decision Problems ◽

Markov Decision Problems ◽

Markov Decision

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Optimal control and optimal sensor activation for Markov decision problems with costly observations

2015 IEEE Conference on Control Applications (CCA) ◽

10.1109/cca.2015.7320814 ◽

2015 ◽

Cited By ~ 1

Author(s):

Rene K. Boel ◽

Jan H. van Schuppen

Keyword(s):

Optimal Control ◽

Decision Problems ◽

Markov Decision Problems ◽

Markov Decision ◽

Sensor Activation

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A simulation-based learning automata framework for solving semi-Markov decision problems under long-run average reward

IIE Transactions ◽

10.1080/07408170490438672 ◽

2004 ◽

Vol 36 (6) ◽

pp. 557-567 ◽

Cited By ~ 14

Author(s):

ABHIJIT GOSAVI ◽

TAPAS K. DAS ◽

SUDEEP SARKAR

Keyword(s):

Learning Automata ◽

Decision Problems ◽

Average Reward ◽

Markov Decision Problems ◽

Long Run ◽

Simulation Based ◽

Markov Decision ◽

Long Run Average Reward

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