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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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Justin L. Balsor,Kathryn M. Murphymplished 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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Computational and Robotic Models of the Hierarchical Organization of Behavior
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Computational and Robotic Models of the Hierarchical Organization of Behavior978-3-642-39875-9
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Computational and Robotic Models of the Hierarchical Organization of Behavior: An Overview, this subject, the open challenges, and promising research directions. Together, the contributions give a good coverage of the most important models, findings, and challenges of the field. This introductory chapter presents the general aims and scope of the book and briefly summarises the contents o
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Hierarchies for Embodied Action Perceptiontion mechanisms, underlying the agent’s ability to add new behaviours to its repertoire. Based on these factors, we review multiple instantiations of a hierarchically-organised biologically-inspired framework for embodied action perception, demonstrating its flexibility in addressing the rich comput
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Learning and Coordinating Repertoires of Behaviors with Common Reward: Credit Assignment and Module ther times avoidance of several predators may be required. The individual modules have separate state representations, i.e. they obtain different inputs but have to carry out actions jointly in the common action space of the agent. Only a single measure of success is observed, which is the sum of th
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The Hierarchical Accumulation of Knowledge in the Distributed Adaptive Control Architectureed on its highest cognitive layer where knowledge is constructed and used. We investigate the roles of reactive and contextual control depending on the characteristics and complexity of the tasks. We also show how multi-sensor information could be integrated in order to acquire and use knowledge opt
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