Results 11 to 20 of about 12,894,975 (292)

A Weighted Markov Decision Process [PDF]

open access: yesOperations Research, 1992
The two most commonly considered reward criteria for Markov decision processes are the discounted reward and the long-term average reward. The first tends to “neglect” the future, concentrating on the short-term rewards, while the second one tends to do the opposite.
Krass, D, Filar, JA, Sinha, SS
openaire   +4 more sources

Quantum logic gate synthesis as a Markov decision process

open access: yesnpj Quantum Information, 2023
Reinforcement learning has witnessed recent applications to a variety of tasks in quantum programming. The underlying assumption is that those tasks could be modeled as Markov decision processes (MDPs).
M. Sohaib Alam   +2 more
doaj   +1 more source

A Markov Decision Process with Awareness and Present Bias in Decision-Making

open access: yesMathematics, 2023
We propose a Markov Decision Process Model that blends ideas from Psychological research and Economics to study decision-making in individuals with self-control problems.
Federico Bizzarri   +2 more
doaj   +1 more source

Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems Part 2—Applications in Transportation, Industries, Communications and Networking and More Topics

open access: yesMachine Learning and Knowledge Extraction, 2021
The two-part series of papers provides a survey on recent advances in Deep Reinforcement Learning (DRL) for solving partially observable Markov decision processes (POMDP) problems.
Xuanchen Xiang, Simon Foo, Huanyu Zang
doaj   +1 more source

Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems: Part 1—Fundamentals and Applications in Games, Robotics and Natural Language Processing

open access: yesMachine Learning and Knowledge Extraction, 2021
The first part of a two-part series of papers provides a survey on recent advances in Deep Reinforcement Learning (DRL) applications for solving partially observable Markov decision processes (POMDP) problems.
Xuanchen Xiang, Simon Foo
doaj   +1 more source

Quantile Markov decision process

open access: yes, 2020
The goal of a traditional Markov decision process (MDP) is to maximize expected cumulative reward over a defined horizon (possibly infinite). In many applications, however, a decision maker may be interested in optimizing a specific quantile of the ...
Li, Xiaocheng   +2 more
core   +4 more sources

Logistic Markov Decision Processes [PDF]

open access: yesProceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
User modeling in advertising and recommendation has typically focused on myopic predictors of user responses. In this work, we consider the long-term decision problem associated with user interaction. We propose a concise specification of long-term interaction dynamics by combining factored dynamic Bayesian networks with logistic predictors of user ...
Martin Mladenov   +5 more
openaire   +2 more sources

Health Status-Based Predictive Maintenance Decision-Making via LSTM and Markov Decision Process

open access: yesMathematics, 2022
Maintenance decision-making is essential to achieve safe and reliable operation with high performance for equipment. To avoid unexpected shutdown and increase machine life as well as system efficiency, it is fundamental to design an effective maintenance
Pan Zheng   +4 more
doaj   +1 more source

On Cognitive Searching Optimization in Semi-Markov Jump Decision Using Multistep Transition and Mental Rehearsal

open access: yesComplexity, 2021
Cognitive searching optimization is a subconscious mental phenomenon in decision making. Aroused by exploiting accessible human action, alleviating inefficient decision and shrinking searching space remain challenges for optimizing the solution space ...
Bingxuan Ren, Tangwen Yin, Shan Fu
doaj   +1 more source

Efficient qualitative analysis of classes of recursive markov decision processes and simple stochastic games [PDF]

open access: yes, 2006
. Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs) are natural models for recursive systems involving both probabilistic and non-probabilistic actions.
Mihalis Yannakakis   +3 more
core   +1 more source

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