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Neural Networks and Animal Behavior
Magnus Enquist & Stefano Ghirlanda

Book Description | Reviews
Chapter 1 [in PDF format]

TABLE OF CONTENTS:

Preface vii
Chapter 1. Understanding Animal Behavior 1
1.1 The causes of behavior 2
1.2 A framework for models of behavior 4
1.3 The structure of behavior models 7
1.4 Neural network models 18
Chapter 2. Fundamentals of Neural Network Models 31
2.1 Network nodes 31
2.2 Network architectures 39
2.3 Achieving specific input-output mappings 45
2.4 Organizing networks without specific guidance 57
2.5 Working with your own models 58
Chapter 3. Mechanisms of Behavior 67
3.1 Analysis of behavior systems 67
3.2 Building neural network models 70
3.3 Reactions to stimuli 75
3.4 Sensory processing 89
3.5 Temporal patterns 96
3.6 Many sources of information and messy information 99
3.7 Central mechanisms of decision making 100
3.8 Motor control 115
3.9 Consequences of damage to nervous systems 123
Chapter 4. Learning and Ontogeny 129
4.1 What are learning and ontogeny? 129
4.2 General aspects of learning 130
4.3 Network models of general learning phenomena 141
4.4 Behaviorally silent learning 151
4.5 Comparison with animal learning theory 155
4.6 Training animals versus training networks 159
4.7 Ontogeny 160
4.8 Conclusions 170
Chapter 5. Evolution 173
5.1 The evolution of behavior systems 173
5.2 Requirements for evolving behavior mechanisms 175
5.3 The material basis of behavioral evolution 178
5.4 Exploring evolution with neural network models 186
5.5 Conclusions 202
Chapter 6. Conclusions 205
6.1 Are neural networks good models of behavior? 205
6.2 Do we use too simple network models? 208
6.3 Comparisons with other models 208
6.4 Neural networks and animal cognition 210
6.5 Final words 218
Bibliography 219
Index 249

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File created: 7/11/2014

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