Modeling Hydra Behavior Using Methods Founded in Behavior-Based Robotics

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viTable of Contents6 Models and methods 216.1 The simulated system . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216.1.1 Movement patterns . . . . . . . . . . . . . . . . . . . . . . . . . 226.1.2 Exteroceptive sensory system . . . . . . . . . . . . . . . . . . . 236.1.3 Proprioceptive sensory system . . . . . . . . . . . . . . . . . . . 236.1.4 Motivational state . . . . . . . . . . . . . . . . . . . . . . . . . . 246.1.5 Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246.1.6 Model parameters . . . . . . . . . . . . . . . . . . . . . . . . . . 256.2 Behavioral organizer . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256.2.1 Applicability clause . . . . . . . . . . . . . . . . . . . . . . . . 266.2.2 Transfer function . . . . . . . . . . . . . . . . . . . . . . . . . . 266.3 Constituent behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 Results and discussion 297.1 Generation of behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . 297.1.1 B1: Spontaneous actions . . . . . . . . . . . . . . . . . . . . . . 307.1.2 B2: Respond to mechanical stimulus . . . . . . . . . . . . . . . . 317.1.3 B3: Respond to light stimulus . . . . . . . . . . . . . . . . . . . 377.1.4 B4: Feeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387.2 Generation of behavioral organizer . . . . . . . . . . . . . . . . . . . . . 407.2.1 Experiment A: Spontaneous locomotion patterns . . . . . . . . . 407.2.2 Experiment B: Effect of starvation on contraction frequency . . . 408 Summary and conclusions 45Bibliography 47A Evolutionary algorithms 53A.1 Encoding scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53A.2 Fitness function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54A.3 Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54A.4 Crossover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55A.5 Mutations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55A.6 Elitism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Table of ContentsviiB Recurrent neural networks 57B.1 Network equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57B.2 Learning algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Page 1: Modeling Hydra Behavior Using Metho
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Page 11: Table of Contents1 Introduction 11.
Page 16 and 17: 2 Chapter 1. Introductione.g. in [1
Page 18 and 19: 4 Chapter 1. Introduction1.3 Outlin
Page 20 and 21: 6 Chapter 2. NotationUpper-case let
Page 22 and 23: 8 Chapter 3. Animal behaviorPsychol
Page 24 and 25: 10 Chapter 3. Animal behaviorperiod
Page 27 and 28: Chapter 4Behavior-based roboticsAs
Page 29 and 30: Chapter 5HydraThis chapter presents
Page 31 and 32: 5.1. Hydra as a model organism 17ce
Page 33 and 34: Chapter 6Models and methodsIn this
Page 35 and 36: 6.1. The simulated system 21Contrac
Page 37 and 38: 6.1. The simulated system 23Table 6
Page 39 and 40: 6.3. Constituent behaviors 25Releas
Page 41 and 42: Chapter 7Results and discussionIn t
Page 43 and 44: 7.1. Generation of behaviors 29Expe
Page 45 and 46: 7.1. Generation of behaviors 31wher
Page 47 and 48: 7.1. Generation of behaviors 33....
Page 49 and 50: 7.1. Generation of behaviors 35Tabl
Page 51 and 52: 7.1. Generation of behaviors 374504
Page 53 and 54: 7.1. Generation of behaviors 39Tran
Page 55 and 56: 7.2. Generation of behavioral organ
Page 57: 7.2. Generation of behavioral organ
Page 60 and 61: 46 Chapter 8. Summary and conclusio
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48 Bibliography[11] BÄCK, T., FOGE
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50 Bibliography[41] MITCHELL, M., A
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52 Bibliography[69] WATSON, J., Beh
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54 Appendix A. Evolutionary algorit
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Appendix BRecurrent neural networks
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Appendix B. Recurrent neural networ
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