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   Articles with "partially observable" as a keyword



Composition of Partially-Observable Services

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2018.2885948

Abstract: In this paper, we tackle the problem of controlling the behavior of independent, partially observable services so that they collectively achieve a desired behavior (specification). The solution consists of synthesizing an orchestrator to coordinate the… read more here.

Keywords: partially observable; observable services; problem; composition partially ... See more keywords

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

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recommendations! Published in 2021 at "IEEE Access"

DOI: 10.1109/access.2021.3131772

Abstract: 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… read more here.

Keywords: reinforcement learning; partially observable; actor critic; approach ... See more keywords

Indirect NRDF for Partially Observable Gauss–Markov Processes With MSE Distortion: Characterizations and Optimal Solutions

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recommendations! Published in 2024 at "IEEE Transactions on Automatic Control"

DOI: 10.1109/tac.2024.3364028

Abstract: We study the problem of characterizing and computing the Gaussian nonanticipative rate-distortion function (NRDF) of partially observable multivariate Gauss–Markov processes with mean-squared error (MSE) distortion constraints. First, we extend Witsenhausen's “tensorization” approach originally used for… read more here.

Keywords: time; distortion; gauss markov; partially observable ... See more keywords

A Partially Observable Markov-Decision-Process-Based Blackboard Architecture for Cognitive Agents in Partially Observable Environments

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recommendations! Published in 2022 at "IEEE Transactions on Cognitive and Developmental Systems"

DOI: 10.1109/tcds.2020.3034428

Abstract: Partial observability, or the inability of an agent to fully observe the state of its environment, exists in many real-world problem domains. However, most cognitive architectures do not have a theoretical foundation that allows for… read more here.

Keywords: partially observable; blackboard architecture; markov decision; observable markov ... See more keywords

Data-Driven Distributed Output Consensus Control for Partially Observable Multiagent Systems

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recommendations! Published in 2019 at "IEEE Transactions on Cybernetics"

DOI: 10.1109/tcyb.2017.2788819

Abstract: This paper is concerned with a class of optimal output consensus control problems for discrete linear multiagent systems with the partially observable system state. Since the optimal control policy depends on the full system state… read more here.

Keywords: system; control; partially observable; output ... See more keywords
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Multi-Agent Reinforcement Learning for Energy Harvesting Two-Hop Communications With a Partially Observable System State

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recommendations! Published in 2021 at "IEEE Transactions on Green Communications and Networking"

DOI: 10.1109/tgcn.2020.3026453

Abstract: We consider an energy harvesting (EH) transmitter communicating with a receiver through an EH relay. The harvested energy is used for data transmission, including the circuit energy consumption. As in practical scenarios, the system’s state,… read more here.

Keywords: partially observable; system state; energy harvesting; energy ... See more keywords

Partially Observable Markov Decision Processes in Robotics: A Survey

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recommendations! Published in 2022 at "IEEE Transactions on Robotics"

DOI: 10.1109/tro.2022.3200138

Abstract: Noisy sensing, imperfect control, and environment changes are defining characteristics of many real-world robot tasks. The partially observable Markov decision process (POMDP) provides a principled mathematical framework for modeling and solving robot decision and control… read more here.

Keywords: partially observable; robotics; observable markov; survey ... See more keywords

SECaaS-Based Partially Observable Defense Model for IIoT Against Advanced Persistent Threats

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recommendations! Published in 2024 at "IEEE Transactions on Services Computing"

DOI: 10.1109/tsc.2024.3422870

Abstract: With the advancement of intelligent and networked technology, the Industrial Internet of Things (IIoT) faces an escalating threat from cyberattacks, especially by Advanced Persistent Threat (APT) attacks. These novel and complex attacks, characterized by their… read more here.

Keywords: defense strategies; iiot; model; partially observable ... See more keywords

ARReSVG: Intelligent Multi-AAV Navigation in Partially Observable Spaces Using Adaptive Deep Reinforcement Learning Approach

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recommendations! Published in 2025 at "IEEE Transactions on Vehicular Technology"

DOI: 10.1109/tvt.2025.3573898

Abstract: Autonomous Aerial Vehicles (AAVs) have brought about a revolution in various applications worldwide. Applications such as aerial surveillance, search and rescue, and operations beyond the line of sight rely on the autonomous navigation capabilities of… read more here.

Keywords: navigation; observable spaces; partially observable; deep reinforcement ... See more keywords

Underwater chemical plume tracing based on partially observable Markov decision process

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recommendations! Published in 2019 at "International Journal of Advanced Robotic Systems"

DOI: 10.1177/1729881419831874

Abstract: Chemical plume tracing based on autonomous underwater vehicle uses chemical as a guidance to navigate and search in the unknown environments. To solve the key issue of tracing and locating the source, this article proposes… read more here.

Keywords: observable markov; partially observable; markov decision; chemical plume ... See more keywords

Adaptive Compensation for Robotic Joint Failures Using Partially Observable Reinforcement Learning

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recommendations! Published in 2024 at "Algorithms"

DOI: 10.3390/a17100436

Abstract: Robotic manipulators are widely used in various industries for complex and repetitive tasks. However, they remain vulnerable to unexpected hardware failures. In this study, we address the challenge of enabling a robotic manipulator to complete… read more here.

Keywords: partially observable; adaptive compensation; joint failures; reinforcement learning ... See more keywords