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Advanced Search Results For "REINFORCEMENT learning"

1 - 10 of 30,227 results for
 "REINFORCEMENT learning"
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Spatial preferences account for inter-animal variability during the continual learning of a dynamic cognitive task.

Publication Type:Academic Journal

Source(s):Cell reports [Cell Rep] 2022 Apr 19; Vol. 39 (3), pp. 110708.

Abstract:Understanding the complexities of behavior is necessary to interpret neurophysiological data and establish animal models of neuropsychiatric disease. This understanding requires knowledge of the underlying information-processing structure-something oft...

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Superstitious learning of abstract order from random reinforcement.

Publication Type:Academic Journal

Source(s):Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2022 Aug 30; Vol. 119 (35), pp. e2202789119. Date of Electronic Publication: 2022 Aug 23.

Abstract:Humans and other animals often infer spurious associations among unrelated events. However, such superstitious learning is usually accounted for by conditioned associations, raising the question of whether an animal could develop more complex cognitive...

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Human Variation in Error-Based and Reinforcement Motor Learning Is Associated With Entorhinal Volume.

Publication Type:Academic Journal

Source(s):Cerebral cortex (New York, N.Y. : 1991) [Cereb Cortex] 2022 Aug 03; Vol. 32 (16), pp. 3423-3440.

Abstract:Error-based and reward-based processes are critical for motor learning and are thought to be mediated via distinct neural pathways. However, recent behavioral work in humans suggests that both learning processes can be bolstered by the use of cognitive...

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Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning.

Publication Type:Academic Journal

Source(s):Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2022 Aug; Vol. 152, pp. 17-33. Date of Electronic Publication: 2022 Apr 16.

Abstract:Autonomous systems are becoming ubiquitous and gaining momentum within the marine sector. Since the electrification of transport is happening simultaneously, autonomous marine vessels can reduce environmental impact, lower costs, and increase efficienc...

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MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning.

Publication Type:Academic Journal

Source(s):Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2022 Jul; Vol. 151, pp. 34-47. Date of Electronic Publication: 2022 Mar 23.

Abstract:Rapid advancements in deep learning have led to many recent breakthroughs. While deep learning models achieve superior performance, often statistically better than humans, their adoption into safety-critical settings, such as healthcare or self-driving...

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Model-Based Reinforcement Learning with Automated Planning for Network Management.

Publication Type:Academic Journal

Source(s):Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Aug 22; Vol. 22 (16). Date of Electronic Publication: 2022 Aug 22.

Abstract:Reinforcement Learning (RL) comes with the promise of automating network management. However, due to its trial-and-error learning approach, model-based RL (MBRL) is not applicable in some network management scenarios. This paper explores the potential ...

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Sticky me: Self-relevance slows reinforcement learning.

Publication Type:Academic Journal

Source(s):Cognition [Cognition] 2022 Oct; Vol. 227, pp. 105207. Date of Electronic Publication: 2022 Jun 22.

Abstract:A prominent facet of social-cognitive functioning is that self-relevant information is prioritized in perception, attention, and memory. What is not yet understood, however, is whether similar effects arise during learning. In particular, compared to o...

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Human motor learning is robust to control-dependent noise.

Publication Type:Academic Journal

Source(s):Biological cybernetics [Biol Cybern] 2022 Jun; Vol. 116 (3), pp. 307-325. Date of Electronic Publication: 2022 Mar 03.

Abstract:Noises are ubiquitous in sensorimotor interactions and contaminate the information provided to the central nervous system (CNS) for motor learning. An interesting question is how the CNS manages motor learning with imprecise information. Integrating id...

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Selective particle attention: Rapidly and flexibly selecting features for deep reinforcement learning.

Publication Type:Academic Journal

Source(s):Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2022 Jun; Vol. 150, pp. 408-421. Date of Electronic Publication: 2022 Mar 17.

Abstract:Deep Reinforcement Learning (RL) is often criticised for being data inefficient and inflexible to changes in task structure. Part of the reason for these issues is that Deep RL typically learns end-to-end using backpropagation, which results in task-sp...

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Social learning in swarm robotics.

Publication Type:Academic Journal

Source(s):Philosophical transactions of the Royal Society of London. Series B, Biological sciences [Philos Trans R Soc Lond B Biol Sci] 2022 Jan 31; Vol. 377 (1843), pp. 20200309. Date of Electronic Publication: 2021 Dec 13.

Abstract:In this paper, we present an implementation of social learning for swarm robotics. We consider social learning as a distributed online reinforcement learning method applied to a collective of robots where sensing, acting and coordination are performed ...

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