Results 31 to 40 of about 937,585 (275)
Multi-UAV Mapping and Target Finding in Large, Complex, Partially Observable Environments
Remote Sensing, 2023 Coordinating multiple unmanned aerial vehicles (UAVs) for the purposes of target finding or surveying points of interest in large, complex, and partially observable environments remains an area of exploration.
Violet Walker +2 more
doaj +1 more source
Machine 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
Aerospace, 2023 Current electronic warfare jammers and radar countermeasures are characterized by dynamism and uncertainty. This paper focuses on a decision-making framework of radar anti-jamming countermeasures.
Huaixi Xing, Qinghua Xing, Kun Wang
doaj +1 more source
Sensors, 2022 In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection.
Zhen Zhang +3 more
doaj +1 more source
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
Blackwell optimality in Markov decision processes with partial observation [PDF]
The Annals of Statistics, 2002 A Blackwell $\epsilon$-optimal strategy in a Markov Decision Process is a strategy that is $\epsilon$-optimal for every discount factor sufficiently close to 1. We prove the existence of Blackwell $\epsilon$-optimal strategies in finite Markov Decision Processes with partial observation.
Rosenberg, Dinah +2 more
openaire +5 more sources
Distributionally Robust Partially Observable Markov Decision Process with Moment-Based Ambiguity [PDF]
SIAM Journal on Optimization, 2019 We consider a distributionally robust (DR) formulation of partially observable Markov decision process (POMDP), where the transition probabilities and observation probabilities are random and unknown, only revealed at the end of every time step.
Hideaki Nakao, Ruiwei Jiang, Siqian Shen
semanticscholar +1 more source
Experimental Design for Partially Observed Markov Decision Processes [PDF]
SIAM/ASA Journal on Uncertainty Quantification, 2018 39 pages, 3 ...
Leifur Thorbergsson, Giles Hooker
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Charge generation in organic solar cells: Journey toward 20% power conversion efficiency
Aggregate, Volume 3, Issue 6, December 2022., 2022 Herein, a photophysicist's views on charge generation in organic solar cells is discussed. Recent steady‐state and time‐resolved spectroscopic studies regarding the exciton diffusion to donor:acceptor interfaces, charge transfer at the donor:acceptor interface, and long‐range spatial dissociation of charge transfer states are highlighted.
Yasunari Tamai
wiley +1 more source
Partially Observable Risk-Sensitive Markov Decision Processes [PDF]
Mathematics of Operations Research, 2017 We consider the problem of minimizing a certainty equivalent of the total or discounted cost over a finite and an infinite time horizon that is generated by a partially observable Markov decision process (POMDP). In contrast to a risk-neutral decision maker, this optimization criterion takes the variability of the cost into account.
Bäuerle, Nicole, Rieder, Ulrich
openaire +4 more sources