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Titlebook: Computational and Robotic Models of the Hierarchical Organization of Behavior; Gianluca Baldassarre,Marco Mirolli Book 2013 Springer-Verla

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The Hierarchical Organisation of Cortical and Basal-Ganglia Systems: A Computationally-Informed Revil picture that emerges is that the cortical and the basal ganglia systems form two highly-organised hierarchical systems working in close synergy and jointly solving all the challenges of choice, selection, and implementation needed to acquire and express adaptive behaviour.
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Divide and Conquer: Hierarchical Reinforcement Learning and Task Decomposition in Humansmplished by identifying useful subgoal states, and that this might in turn be accomplished through a structural analysis of the given task domain. We review results from a set of behavioral and neuroimaging experiments, in which we have investigated the relevance of these ideas to human learning and
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Book 2013 of the brain. They might even lead to the cumulative acquisition of an ever-increasing number of skills, which seems to be a characteristic of mammals, and humans in particular..This book is a comprehensive overview of the state of the art on the modeling of the hierarchical organization of behavio
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Book 2013t of control architectures and learning algorithms that can support the acquisition and deployment of several different skills, which in turn seems to require a modular and hierarchical organization. In this way, different modules can acquire different skills without catastrophic interference, and h
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Panayiotis Tsokas,Robert D. Blitzercal reinforcement learning to illustrate the influence of behavioral hierarchy on exploration and representation. Beyond illustrating these features, the examples provide support for the central role of behavioral hierarchy in development and learning for both artificial and natural agents.
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Behavioral Hierarchy: Exploration and Representationcal reinforcement learning to illustrate the influence of behavioral hierarchy on exploration and representation. Beyond illustrating these features, the examples provide support for the central role of behavioral hierarchy in development and learning for both artificial and natural agents.
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Peter R. Dunkley,Phillip J. Robinsonand interference is examined together with some interpretations in terms of computational models. Finally, we present some possible approaches to the issue of learning multiple tasks while avoiding catastrophic interference in bio-inspired learning architectures.
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Generalization and Interference in Human Motor Controland interference is examined together with some interpretations in terms of computational models. Finally, we present some possible approaches to the issue of learning multiple tasks while avoiding catastrophic interference in bio-inspired learning architectures.
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