Computational and Robotic Models of the Hierarchical Organization of Behavior
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...
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| Other Authors: | , |
| Language: | English |
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Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2013.
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| Edition: | 1st ed. 2013. |
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| Online Access: | https://doi.org/10.1007/978-3-642-39875-9 |
Table of Contents:
- Chap. 1 - Computational and Robotic Models of the Hierarchical Organization of Behavior: An Overview
- Chap. 2 - Behavioral Hierarchy: Exploration and Representation
- Chap. 3 - Self-organized Functional Hierarchy Through Multiple Timescales: Neurodynamical Accounts for Behavioral Compositionality
- Chap. 4 - Autonomous Representation Learning in a Developing Agent
- Chap. 5 - Hierarchies for Embodied Action Perception
- Chap. 6 - Learning and Coordinating Repertoires of Behaviors with Common Reward: Credit Assignment and Module Activation
- Chap. 7 - Modular, Multimodal Arm Control Models
- Chap. 8 - Generalization and Interference in Human Motor Control
- Chap. 9 - A Developmental Framework for Cumulative Learning Robots
- Chap. 10 - The Hierarchical Accumulation of Knowledge in the Distributed Adaptive Control Architecture
- Chap. 11 - The Hierarchical Organization of Cortical and Basal Ganglia Systems: A Computationally Informed Review and Integrated Hypothesis
- Chap. 12 - Divide and Conquer: Hierarchical Reinforcement Learning and Task Decomposition in Humans
- Chap. 13 - Neural Network Modelling of Hierarchical Motor Function in the Brain
- Chap. 14 - Restoring Purpose in Behavior.