Modeling Hydra Behavior Using Methods Founded in Behavior-Based Robotics

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18 Chapter 5. HydraResponse to light stimulusOn exposure to strong light there is an immediate inhibition of any ongoing contraction.Following a latency, a response consisting of either contraction or locomotion is evoked.As in the case of mechanical stimulus, locomotion is more common in starved animals.The latency is inversely related to light intensity [59]. There is no habituation [53].FeedingThe feeding behavior of Hydra consists of a sequence of actions, namely prey capture,mouth opening, ingestion, digestion, and regurgitation 4 . The behavior is evoked by mechanicalstimulation of Hydra’s tentacles or by the presence of GSH, which is released byprey stung by nematocysts. The behavioral threshold is regulated by Hydra’s nutritionalstate, with starved animals exhibiting a lower threshold than recently fed ones. Also, thereis a refractory period following a feeding response, with the capacity of responding beinggradually regained [32, 33].5.1.4 Behavior coordinationAs described in the literature, feeding inhibits responses to light and mechanical stimuli.In addition, response to light inhibits response to mechanical stimuli, thus forming apriority-based relation of Hydra’s behaviors [32, 54].The behaviors and sub-behaviors of Hydra, as modeled in this project, are summarizedin Tables 5.1 and 5.2 below.Table 5.1: Behaviors shown by Hydra. Priority 1 denotes the highest priority.Label Priority DescriptionB1 4 Spontaneous actionsB2 3 Response to mechanical stimulusB3 2 Response to light stimulusB4 1 FeedingTable 5.2: Sub-behaviors of HydraLabel DescriptionB11, B21, B31 Contraction/ExtensionB12, B22, B32 Locomotion4 Through regurgitation, stomach contents is transfered back into the mouth, and in this way Hydra getsrid of undigested remains of the prey.
Chapter 6Models and methodsIn this thesis the overall behavior of Hydra is modeled by defining individual behaviors,as well as a behavioral organizer for coordination of those behaviors. The model of Hydraaimes at describing the behavior of the animal as functions of its motivational state. Forthe initial purpose of validating the behavioral model, a simulated system was developed.Also, once a behavioral model has been validated, such a system can be used to predictthe behavior of the animal in various environmental set-ups. In this project, however,the simulated system was only used for validation experiments, as discussed in Section7.2. This chapter starts with a description of the simulated system, and concludes bypresenting the methods used for generating and organizing the behaviors of Hydra.6.1 The simulated systemHydra was modeled ignoring the dynamical properties of its body. It should be notedthat, as pointed out e.g. in [10, 12], the body of an animal is indeed connected to itsbehavior. Thus, this simplification was made not because the properties of Hydra’s bodyare unimportant for its behavior, but rather in an attempt to isolate, as much as possible,and focus on the behavioral traits in this first work towards a behavioral model of theanimal. Also, the time aspect of this project was a factor in making this simplification.As will be discussed in Chapter 8, an expansion of the model to include a more realisticmorphology of Hydra might very well be a task for future work.In this simplified model of Hydra, the animal’s body is represented in 2D, by a circlewith radius r and maximum extension length l max . The movement of the animal is controlledsimply by setting the corresponding states directly, which is described in Section6.1.1. The physical state variables describing the body of the simulated Hydra is given inTable 6.1. In the 2D model of Hydra, the position of the animal’s hypostome, rather thanof its foot, was taken as the interface to (the simulated) environment. While this approach19
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Page 22 and 23: 8 Chapter 3. Animal behaviorPsychol
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Page 27 and 28: Chapter 4Behavior-based roboticsAs
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Page 31: 5.1. Hydra as a model organism 17ce
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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
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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
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