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Open AccessJournal ArticleDOI

Learning to represent reward structure: a key to adapting to complex environments.

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TLDR
This work proposes a new hypothesis - the dopamine reward structural learning hypothesis - in which dopamine activity encodes multiplex signals for learning in order to represent reward structure in the internal state, leading to better reward prediction.
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This article is published in Neuroscience Research.The article was published on 2012-12-01 and is currently open access. It has received 30 citations till now. The article focuses on the topics: Reinforcement learning.

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Citations
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Journal ArticleDOI

Prefrontal cortex as a meta-reinforcement learning system

TL;DR: A new theory is presented showing how learning to learn may arise from interactions between prefrontal cortex and the dopamine system, providing a fresh foundation for future research.
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Internally generated sequences in learning and executing goal-directed behavior

TL;DR: Using computational modeling, it is proposed that internally generated sequences may be productively considered a component of goal-directed decision systems, implementing a sampling-based inference engine that optimizes goal acquisition at multiple timescales of on-line choice, action control, and learning.
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Prediction error associated with the perceptual segmentation of naturalistic events

TL;DR: At points of unpredictability, midbrain and striatal regions associated with the phasic release of the neurotransmitter dopamine transiently increased in activity, which could provide a global updating signal, cuing other brain systems that a significant new event has begun.
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Reward feedback accelerates motor learning

TL;DR: The use of reward feedback is a promising approach to either supplement or substitute sensory feedback in the development of improved neurorehabilitation techniques and points to an important role played by reward in the motor learning process.
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Rethinking dopamine as generalized prediction error.

TL;DR: A new theory of dopamine function is developed that embraces a broader conceptualization of prediction errors and indicates that by signalling errors in both sensory and reward predictions, dopamine supports a form of RL that lies between model-based and model-free algorithms.
References
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Journal ArticleDOI

Understanding dopamine and reinforcement learning: The dopamine reward prediction error hypothesis

TL;DR: It is suggested very clearly that the phasic activity of the midbrain dopamine neurons provides a global mechanism for synaptic modification that provides the mechanistic underpinning for a specific class of reinforcement learning mechanisms that now seem to underlie much of human and animal behavior.
ReportDOI

Intrinsically Motivated Reinforcement Learning

TL;DR: Initial results from a computational study of intrinsically motivated reinforcement learning aimed at allowing artificial agents to construct and extend hierarchies of reusable skills that are needed for competent autonomy are presented.
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Parallel neural networks for learning sequential procedures

TL;DR: A hypothetical scheme in which a sequential procedure is acquired independently by two cortical systems, one using spatial coordinates and the other using motor coordinates, which are active preferentially in the early and late stages of learning.
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What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?

Kenji Doya
- 01 Oct 1999 - 
TL;DR: This paper investigates how the learning modules specialized for these three kinds of learning can be assembled into goal-oriented behaving systems and presents a novel view that their computational roles can be characterized by asking what are the "goals" of their computation.
Journal ArticleDOI

Phasic excitation of dopamine neurons in ventral VTA by noxious stimuli

TL;DR: It is shown that dopamine neurons in the dorsal VTA are inhibited by noxious footshocks, consistent with their role in reward processing, and this observation can explain a number of previously confusing findings that suggested a role for dopamine in processing both rewarding and aversive events.
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