A Framework for Modeling Bounded Rationality: Mis-Specified Bayesian-Markov Decision Processes

2016 ◽  
Author(s):  
Ignacio Esponda ◽  
Demian Pouzo
Keyword(s):  
Bounded Rationality ◽  
Markov Decision Processes ◽  
Decision Processes ◽  
Markov Decision

Extreme-point solutions in Markov decision processes

1983 ◽  
Vol 20 (04) ◽  
pp. 835-842
Author(s):  
David Assaf
Keyword(s):  
Convex Function ◽  
Extreme Point ◽  
Markov Decision Processes ◽  
Convex Functions ◽  
Sufficient Conditions ◽  
Decision Processes ◽  
Markov Decision ◽  
Full Solution

The paper presents sufficient conditions for certain functions to be convex. Functions of this type often appear in Markov decision processes, where their maximum is the solution of the problem. Since a convex function takes its maximum at an extreme point, the conditions may greatly simplify a problem. In some cases a full solution may be obtained after the reduction is made. Some illustrative examples are discussed.

scholarly journals Transfer-Entropy-Regularized Markov Decision Processes

2021 ◽  
pp. 1-1
Author(s):  
Takashi Tanaka ◽  
Henrik Sandberg ◽  
Mikael Skoglund
Keyword(s):  
Markov Decision Processes ◽  
Decision Processes ◽  
Transfer Entropy ◽  
Markov Decision

ProbMela and verification of Markov decision processes

2005 ◽  
Vol 32 (4) ◽  
pp. 22-27 ◽  
Author(s):  
Christel Baier ◽  
Frank Ciesinski ◽  
Marcus Größer
Keyword(s):  
Markov Decision Processes ◽  
Decision Processes ◽  
Markov Decision
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