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Computational and Robotic Models of the Hierarchical Organization of Behavior

CMPTNL & ROBOTIC MODELS OF HIERARCHICAL ORGANIZATN BHVR

Information Technology

Computing & Information Technology

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B2B & B2C

Current robots and other artificial systems are typically able to accomplish only one single task. Overcoming this limitation requires the development 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 higher-level components of the system can solve complex tasks by exploiting the skills encapsulated in the lower-level modules. While machine learning and robotics recognize the fundamental importance of the hierarchical organization of behavior for building robots that scale up to solve complex tasks, research in psychology and neuroscience shows increasing evidence that modularity and hierarchy are pivotal organization principles of behavior and 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 behavior in animals, and on its exploitation in robot controllers. The book perspective is highly interdisciplinary, featuring models belonging to all relevant areas, including machine learning, robotics, neural networks, and computational modeling in psychology and neuroscience. The book chapters review the authors' most recent contributions to the investigation of hierarchical behavior, and highlight the open questions and most promising research directions.

POST SECONDARY FOUR YEAR

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Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Contents.
1: Computational and Robotic Models of the Hierarchical Organization of Behavior: An Overview.
2: Hierarchical Organization of Behavior in Robots.
3: Behavioral Hierarchy: Exploration and Representation.
4: Self-Organized Functional Hierarchy through Multiple Timescales: Neuro-dynamical Accounts for Behavioral Compositionality.
5: Autonomous Representation Learning in a Developing Agent.
6: Hierarchies for Embodied Action Perception.
7: Learning and Coordinating Repertoires of Behaviors with Common Reward: Credit Assignment and Module Activation.
8: Hierarchical Organization of Animal Behavior.
9: Modular, Multimodal Arm Control Models.
10: Generalization and Interference in Human Motor Control.
11: A Developmental Framework for Cumulative Learning Robots.
12: The Hierarchical Accumulation of Knowledge in the Distributed Adaptive Control Architecture.
13: Hierarchical Organization of Animal Brain.
14: The Hierarchical Organisation of Cortical and Basal-Ganglia Systems: A Computationally-Informed Review and Integrated Hypothesis.
15: Divide and Conquer: Hierarchical Reinforcement Learning and Task Decomposition in Humans.
16: Neural Network Modelling of Hierarchical Motor Function in the Brain.
17: Restoring Purpose in Behavior.
Index.

Computational and Robotic Models of the Hierarchical Organization of Behavior.css-1p8rvzy{position:absolute;padding-left:8px;}

Computational and Robotic Models of the Hierarchical Organization of Behavior