Modeling Hydra Behavior Using Methods Founded in Behavior-Based Robotics

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36 Chapter 7. Results and discussionFigure 7.5: Response strength for best evolved integrator habituation model. ISIs in time-steps.Example of contraction response to mechanical stimulus1Transfer function during B20.80.60.40.2Set of ACLatencyContraction pulseReset of AC00 2 4 6 8 10 12 14 16 18 20Time [s]Figure 7.6: Example of output from transfer function during response to mechanical stimulus.
7.1. Generation of behaviors 37450400Latency vs. stimulus intensityMeasured dataFunction approximation350Reaction time [s]3002502001501005000 10 20 30 40 50 60 70 80 90 100Relative light intensity [%]Figure 7.7: Latency of response to light stimulus. In the function fitting, the measured responseto 6% relative stimulus intensity was considered an outlier.7.1.3 B3: Respond to light stimulusSimilar to B2, response occurs by contraction or by locomotion. As discussed in Section5.1.3, upon exposure to light, there is an immediate inhibition of any ongoing contraction.Following a latency which depend on stimulus intensity, a response is evoked. There isno habituation to repeated stimulus.Applicability clauseAs with B2, an event-driven AC was used. Activation of the AC occurs if M l > T l , whereT l was set to 0.2. The latency was modeled to fit the data obtained in [59]. Least squarefunction fitting was used, and the latency obtained wasL l = 24.15M l. (7.11)Fig. 7.7 illustrates the result obtained. Note that the measured data is a function of relativestimulus intensity in percent, whereas readings from the light sensor in the modeled Hydraare taken in [0, 1]. The activation threshold, T l , also ensures that division by zero does notoccur in the calculations of L l .
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Page 11 and 12: Table of Contents1 Introduction 11.
Page 13: Table of ContentsviiB Recurrent neu
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: 7.1. Generation of behaviors 35Tabl
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
Page 62 and 63: 48 Bibliography[11] BÄCK, T., FOGE
Page 64 and 65: 50 Bibliography[41] MITCHELL, M., A
Page 66 and 67: 52 Bibliography[69] WATSON, J., Beh
Page 68 and 69: 54 Appendix A. Evolutionary algorit
Page 71 and 72: Appendix BRecurrent neural networks
Page 73: Appendix B. Recurrent neural networ

Modeling Hydra Behavior Using Methods Founded in Behavior-Based Robotics

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