Results 11 to 20 of about 35,395 (320)

History-dependent Evaluations in Partially Observable Markov Decision Process [PDF]

SIAM Journal on Control and Optimization, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xavier Mathieu Raymond Venel, Bruno Ziliotto   +1 more
openaire   +5 more sources

Recursively-Constrained Partially Observable Markov Decision Processes [PDF]

, 2023
Many sequential decision problems involve optimizing one objective function while imposing constraints on other objectives. Constrained Partially Observable Markov Decision Processes (C-POMDP) model this case with transition uncertainty and partial observability.
Ho, Qi Heng, Becker, Tyler, Kraske, Benjamin, Laouar, Zakariya, Feather, Martin S., Rossi, Federico, Lahijanian, Morteza, Sunberg, Zachary N.   +7 more
openaire   +3 more sources

Joint Optimal Policy for Maintenance, Spare Unit Selection and Inventory Control Under a Partially Observable Markov Decision Process [PDF]

Mathematics
This research investigates the joint optimization of maintenance and spare unit management for series systems composed of multiple heterogeneous units.
Nozomu Ogura, Mizuki Kasuya, Lu Jin
doaj   +2 more sources

A Corrosion Maintenance Model Using Continuous State Partially Observable Markov Decision Process for Oil and Gas Pipelines

Algorithms, 2023
This paper proposes a continuous state partially observable Markov decision process (POMDP) model for the corrosion maintenance of oil and gas pipelines.
Ezra Wari, Weihang Zhu, Gino Lim
doaj   +1 more source

Decentralized Control of Partially Observable Markov Decision Processes using Belief Space Macro-actions [PDF]

, 2015
The focus of this paper is on solving multi-robot planning problems in continuous spaces with partial observability. Decentralized partially observable Markov decision processes (Dec-POMDPs) are general models for multi-robot coordination problems, but ...
Agha-mohammadi, Ali-akbar, Amato, Christopher, How, Jonathan P., Omidshafiei, Shayegan   +3 more
core   +7 more sources

Guided Soft Actor Critic: A Guided Deep Reinforcement Learning Approach for Partially Observable Markov Decision Processes

IEEE Access, 2021
Most real-world problems are essentially partially observable, and the environmental model is unknown. Therefore, there is a significant need for reinforcement learning approaches to solve them, where the agent perceives the state of the environment ...
Mehmet Haklidir, Hakan Temeltas
doaj   +1 more source

Experimental Design for Partially Observed Markov Decision Processes [PDF]

SIAM/ASA Journal on Uncertainty Quantification, 2018
39 pages, 3 ...
Thorbergsson, Leifur, Hooker, Giles
openaire   +3 more sources

Quantum partially observable Markov decision processes [PDF]

Physical Review A, 2014
We present quantum observable Markov decision processes (QOMDPs), the quantum analogs of partially observable Markov decision processes (POMDPs). In a QOMDP, an agent is acting in a world where the state is represented as a quantum state and the agent can choose a superoperator to apply. This is similar to the POMDP belief state, which is a probability
Barry, Jennifer, Barry, Daniel T., Aaronson, Scott   +2 more
openaire   +2 more sources

Structural Estimation of Partially Observable Markov Decision Processes

IEEE Transactions on Automatic Control, 2023
In many practical settings control decisions must be made under partial/imperfect information about the evolution of a relevant state variable. Partially Observable Markov Decision Processes (POMDPs) is a relatively well-developed framework for modeling and analyzing such problems.
Yanling Chang, Alfredo Garcia, Zhide Wang, Lu Sun   +3 more
openaire   +2 more sources

Entropy Maximization for Partially Observable Markov Decision Processes

IEEE Transactions on Automatic Control, 2022
14 pages, 10 figures.
Yagiz Savas, Michael Hibbard, Bo Wu, Takashi Tanaka, Ufuk Topcu   +4 more
openaire   +3 more sources