Results 11 to 20 of about 48,213 (289)

Controllable Summarization with Constrained Markov Decision Process

open access: yesTransactions of the Association for Computational Linguistics, 2021
We study controllable text summarization, which allows users to gain control on a particular attribute (e.g., length limit) of the generated summaries. In this work, we propose a novel training framework based on Constrained Markov Decision Process (CMDP)
Hou Pong Chan, Lu Wang, Irwin King
doaj   +1 more source

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

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

Risk-Sensitive Markov Decision Processes of USV Trajectory Planning with Time-Limited Budget

open access: yesSensors, 2023
Trajectory planning plays a crucial role in ensuring the safe navigation of ships, as it involves complex decision making influenced by various factors. This paper presents a heuristic algorithm, named the Markov decision process Heuristic Algorithm (MHA)
Yi Ding, Hongyang Zhu
doaj   +1 more source

Automatic Horizon Picking Using Multiple Seismic Attributes and Markov Decision Process

open access: yesRemote Sensing, 2023
Picking the reflection horizon is an important step in velocity inversion and seismic interpretation. Manual picking is time-consuming and no longer suitable for current large-scale seismic data processing.
Chengliang Wu   +5 more
doaj   +1 more source

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