Neural Network Perspectives on Cognition and Adaptive Robotics
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adaptive robotic systems
Artificial Neural Network Controller
Brittleness Problem
Case Role Assignment
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Cellular Automata
Center Embeddings
Central Pattern Generator
Commonsense Reasoning
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Gill Withdrawal Reflex
Hidden Layer Representation
Hidden Unit
human cognition
Intrinsic Computation
Learning Samples
neural computing techniques
Neural Controller
neural network architectures
RAAM
Random Dot Stereograms
Reflex Responses
Sensory Motor Loops
Simulator Time Unit
SRN
Structure Sensitive Processes
Subsymbolic Representations
Symbolic Ai
Time Dependent Constraint
Variable Binding
Weight Vector
Product details
- ISBN 9780367455873
- Weight: 453g
- Dimensions: 156 x 234mm
- Publication Date: 02 Dec 2019
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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Featuring an international team of authors, Neural Network Perspectives on Cognition and Adaptive Robotics presents several approaches to the modeling of human cognition and language using neural computing techniques. It also describes how adaptive robotic systems can be produced using neural network architectures. Covering a wide range of mainstream area and trends, each chapter provides the latest information from a different perspective.
Antony Browne
