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   Articles with "action space" as a keyword



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Complete representation of action space and value in all dorsal striatal pathways.

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recommendations! Published in 2021 at "Cell reports"

DOI: 10.1016/j.celrep.2021.109437

Abstract: The dorsal striatum plays a central role in the selection, execution, and evaluation of actions. An emerging model attributes action selection to the matrix and evaluation to the striosome compartment. Here, we use large-scale cell-type-specific… read more here.

Keywords: value; complete representation; action space; dorsal ... See more keywords

Recommendation of deep reinforcement learning based on value function considering error reduction

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-18926-7

Abstract: Deep reinforcement learning (DRL) algorithms have been widely applied in user cold-start recommender systems because they can gradually capture users’ dynamic interest preferences. Deep Q-Networks (DQN) have become the most popular reinforcement learning (RL) method… read more here.

Keywords: error; reinforcement learning; action space; action ... See more keywords

Box/peanut-shaped bulges in action space

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recommendations! Published in 2020 at "Monthly Notices of the Royal Astronomical Society"

DOI: 10.1093/mnras/staa2568

Abstract: Abstract We introduce the study of box/peanut (B/P) bulges in the action space of the initial axisymmetric system. We explore where populations with different actions end up once a bar forms and a B/P bulge… read more here.

Keywords: action space; metallicity; box peanut; action ... See more keywords
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D3PG: Dirichlet DDPG for Task Partitioning and Offloading with Constrained Hybrid Action Space in Mobile Edge Computing

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recommendations! Published in 2022 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2022.3166110

Abstract: Mobile Edge Computing (MEC) has been regarded as a promising paradigm to reduce service latency for data processing in Internet of Things, by provisioning computing resources at network edge. In this work, we jointly optimize… read more here.

Keywords: task partitioning; edge; hybrid action; action space ... See more keywords

FLIRRAS: Fast Learning With Integrated Reward and Reduced Action Space for Online Multitask Offloading

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recommendations! Published in 2023 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2022.3222295

Abstract: With the rapid development of edge data intelligence, task offloading (TO) and resource allocation (RA) optimization in multiaccess edge computing networks can significantly improve the Quality of Service (QoS). However, for the online scenario, traditional… read more here.

Keywords: fast learning; action space; learning integrated; space ... See more keywords

Learning Target-Oriented Push-Grasping Synergy in Clutter With Action Space Decoupling

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recommendations! Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3204822

Abstract: We explore a method for grasping novel target objects through push-grasping synergy in a cluttered environment without using object detection and segmentation algorithms. The target information is represented by a color heightmap of the target… read more here.

Keywords: action space; action; push grasping; position ... See more keywords

Motion Primitives as the Action Space of Deep Q-Learning for Planning in Autonomous Driving

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recommendations! Published in 2024 at "IEEE Transactions on Intelligent Transportation Systems"

DOI: 10.1109/tits.2024.3436530

Abstract: Motion planning for autonomous vehicles is commonly implemented via graph-search methods, which pose limitations to the model accuracy and environmental complexity that can be handled under real-time constraints. In contrast, reinforcement learning, specifically the deep… read more here.

Keywords: motion; motion primitives; planning autonomous; action space ... See more keywords

Discretizing Continuous Action Space With Unimodal Probability Distributions for On-Policy Reinforcement Learning

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recommendations! Published in 2024 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2024.3446371

Abstract: For on-policy reinforcement learning (RL), discretizing action space for continuous control can easily express multiple modes and is straightforward to optimize. However, without considering the inherent ordering between the discrete atomic actions, the explosion in… read more here.

Keywords: probability; action space; probability distributions; policy ... See more keywords

Resilient Path Tracking of Autonomous Driving under Few-shot Action Space Attacks

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recommendations! Published in 2025 at "ACM Transactions on Cyber-Physical Systems"

DOI: 10.1145/3777460

Abstract: Modern autonomous vehicles face growing cybersecurity risks, especially from action space attacks that directly target vehicle actuators. This paper systematically evaluates the resilience of three representative autonomous driving (AD) architectures, including modular, end-to-end, and feature-fused… read more here.

Keywords: shot action; space attacks; autonomous driving; action space ... See more keywords

The Interrelation Between Peripersonal Action Space and Interpersonal Social Space: Psychophysiological Evidence and Clinical Implications

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recommendations! Published in 2021 at "Frontiers in Human Neuroscience"

DOI: 10.3389/fnhum.2021.636124

Abstract: The peripersonal space is an adaptive and flexible interface between the body and the environment that fulfills a dual-motor function: preparing the body for voluntary object-oriented actions to interact with incentive stimuli and preparing the… read more here.

Keywords: peripersonal action; space; social space; space interpersonal ... See more keywords

A Generalized Deep Reinforcement Learning Model for Distribution Network Reconfiguration with Power Flow-Based Action-Space Sampling

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recommendations! Published in 2024 at "Energies"

DOI: 10.3390/en17205187

Abstract: Distribution network reconfiguration (DNR) is used by utilities to enhance power system performance in various ways, such as reducing line losses. Conventional DNR algorithms rely on accurate values of network parameters and lack scalability and… read more here.

Keywords: action space; distribution network; reconfiguration; network ... See more keywords