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Embodied and Situated Agents, Adaptive Behavior in

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Computational Complexity
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Article Outline

Glossary

Definition of the Subject

Introduction

Embodiment and Situatedness

Behavior and Cognition as Complex Adaptive Systems

Adaptive Methods

Evolutionary Robotics Methods

Discussion and Conclusion

Bibliography

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Abbreviations

Phylogenesis:

Indicates the variations of the genetic characteristics of a population of artificial agents throughout generations.

Ontogenesys:

Indicates the variations which occur in the phenotypical characteristics of an artificial agent (i. e. in the characteristics of the control system or of the body of the agent) while it interacts with the environment.

Embodied agent:

Indicates an artificial system (simulated or physical) which has a body (characterized by physical properties such us shape, dimension, weight, etc), actuators (e. g. motorized wheels, motorized articulated joints), and sensors (e. g. touch sensors or vision sensors). For a more restricted definition see the concluding section of the paper.

Situated agent:

Indicates an artificial system which is located in a physical environment (simulated or real) with which it interacts on the basis of the law of physics. For a more restricted definition see the concluding section of the paper.

Morphological computation:

Indicates the ability of the body of an agent (with certain specific characteristics) to control its interaction with the environment so to produce a given desired behavior.

Bibliography

  1. Asada M, MacDorman K, Ishiguro H, Kuniyoshi Y (2001) Cognitive developmentalrobotics as a new paradigm for the design of humanoid robots. Robot Auton Syst 37:185–193

    Article  MATH  Google Scholar 

  2. Baldassarre G, Parisi D, Nolfi S (2006) Distributed coordination of simulatedrobots based on self‐organisation. Artif Life 3(12):289–311

    Article  Google Scholar 

  3. Beer RD (1995) A dynamical systems perspective on agent‐environmentinteraction. Artif Intell 72:173–215

    Article  Google Scholar 

  4. Beer RD (2003) The dynamics of active categorical perception in an evolved model agent. Adapt Behav 11:209–243

    Article  Google Scholar 

  5. Berthouze L, Lungarella M (2004) Motor skill acquisition under environmentalperturbations: on the necessity of alternate freezing and freeing. Adapt Behav 12(1):47–63

    Article  Google Scholar 

  6. Bongard JC, Paul C (2001) Making evolution an offer it can't refuse: Morphologyand the extradimensional bypass. In: Keleman J, Sosik P (eds) Proceedings of the Sixth European Conference on Artificial Life. Lecture Notes in ArtificialIntelligence, vol 2159. Springer, Berlin

    Google Scholar 

  7. Breazeal C (2003) Towards sociable robots. Robotics Auton Syst42(3–4):167–175

    Article  MATH  Google Scholar 

  8. Brooks RA (1991) Intelligence without reason. In: Mylopoulos J, Reiter R (eds)Proceedings of 12th International Joint Conference on Artificial Intelligence. Morgan Kaufmann, San Mateo

    Google Scholar 

  9. Brooks RA (1991) Intelligence without reason. In: Proceedings of 12thInternational Joint Conference on Artificial Intelligence. Sydney, Australia, pp 569–595

    Google Scholar 

  10. Brooks RA, Breazeal C, Irie R, Kemp C, Marjanovic M, Scassellati B, Williamson M(1998) Alternate essences of intelligence. In: Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), Madison, Wisconsin,pp 961–976

    Google Scholar 

  11. Chiel HJ, Beer RD (1997) The brain has a body: Adaptive behavior emergesfrom interactions of nervous system, body and environment. Trends Neurosci 20:553–557

    Article  Google Scholar 

  12. Clark A (1997) Being there: Putting brain, body and world togetheragain. MIT Press, Cambridge

    Google Scholar 

  13. Endo I, Yamasaki F, Maeno T, Kitano H (2002) A method forco‐evolving morphology and walking patterns of bipedhumanoid robot. In: Proceedings of the IEEE Conference on Robotics andAutomation, Washington, D.C.

    Google Scholar 

  14. Floreano D, Husband P, Nolfi S (2008) Evolutionary Robotics. In: SicilianoB, Oussama Khatib (eds) Handbook of Robotics. Springer, Berlin

    Google Scholar 

  15. Gigliotta O, Nolfi S (2008) On the coupling between agent internal and agent/environmental dynamics: Development of spatial representations in evolvingautonomous robots. Adapt Behav 16:148–165

    Article  Google Scholar 

  16. Goldenberg E, Garcowski J, Beer RD (2004) May we have your attention: Analysisof a selective attention task. In: Schaal S, Ijspeert A, Billard A, Vijayakumar S, Hallam J, Meyer J-A (eds) From Animals to Animats 8: Proceedingsof the Eighth International Conference on the Simulation of Adaptive Behavior. MIT Press, Cambridge

    Google Scholar 

  17. Harvey I (2000) Robotics: Philosophy of mind using a screwdriver. In:Gomi T (ed) Evolutionary Robotics: From Intelligent Robots to Artificial Life, vol III. AAI Books, Ontario

    Google Scholar 

  18. Holland J (1975) Adaptation in natural and artificial systems. University ofMichigan Press, Ann Arbor

    Google Scholar 

  19. Keijzer F (2001) Representation and behavior. MIT Press,London

    Google Scholar 

  20. Kelso JAS (1995) Dynamics patterns: The self‐organization of brain andbehaviour. MIT Press, Cambridge

    Google Scholar 

  21. Lungarella M, Metta G, Pfeifer R, Sandini G (2003) Developmental robotics:a survey. Connect Sci 15:151–190

    Article  Google Scholar 

  22. Marocco D, Nolfi S (2007) Emergence of communication in embodied agentsevolved for the ability to solve a collective navigation problem. Connect Sci 19(1):53–74

    Article  Google Scholar 

  23. Massera G, Cangelosi A, Nolfi S (2007) Evolution of prehension ability in ananthropomorphic neurorobotic arm. Front Neurorobot 1(4):1–9

    Google Scholar 

  24. McGeer T (1990) Passive walking with knees. In: Proceedings of the IEEEConference on Robotics and Automation, vol 2, pp 1640–1645

    Google Scholar 

  25. Metta G, Sandini G, Natale L, Panerai F (2001) Development and Q30robotics. In: Proceedings of IEEE-RAS International Conference on Humanoid Robots, pp 33–42

    Google Scholar 

  26. Mondada F, Franzi E, Ienne P (1993) Mobile robot miniaturisation: A toolfor investigation in control algorithms. In: Proceedings of the Third International Symposium on Experimental Robotics, Kyoto,Japan

    Google Scholar 

  27. Mondada F, Pettinaro G, Guigrard A, Kwee I, Floreano D, Denebourg J-L, NolfiS, Gambardella LM, Dorigo M (2004) Swarm-bot: A new distributed robotic concept. Auton Robots17(2–3):193–221

    Article  Google Scholar 

  28. Nolfi S (2002) Power and limits of reactive agents. Neurocomputing49:119–145

    Article  Google Scholar 

  29. Nolfi S (2005) Behaviour as a complex adaptive system: On the role ofself‐organization in the development of individual and collective behaviour. Complexus 2(3–4):195–203

    Google Scholar 

  30. Nolfi S, Floreano D (1999) Learning and Evolution. Auton Robots1:89–113

    Article  Google Scholar 

  31. Nolfi S, Floreano D (2000) Evolutionary Robotics: The Biology, Intelligence,and Technology of Self‐Organizing Machines. MIT Press/Bradford Books, Cambridge

    Google Scholar 

  32. Nolfi S, Marocco D (2002) Active perception: A sensorimotor account ofobject categorization. In: Hallam B, Floreano D, Hallam J, Hayes G, Meyer J-A (eds) From Animals to Animats 7, Proceedings of the VII InternationalConference on Simulation of Adaptive Behavior. MIT Press, Cambridge, pp 266–271

    Google Scholar 

  33. Oudeyer P-Y, Kaplan F, Hafner V (2007) Intrinsic motivation systems forautonomous mental development. IEEE Trans Evol Comput 11(2):265–286

    Article  Google Scholar 

  34. Pfeifer R, Bongard J (2007) How the body shape the way we think. MIT Press,Cambridge

    Google Scholar 

  35. Pfeifer R, Iida F, Gómez G (2006) Morphological computation for adaptivebehavior and cognition. In: International Congress Series, vol 1291, pp 22–29

    Google Scholar 

  36. Pollack JB, Lipson H, Funes P, Hornby G (2001) Three generations ofcoevolutionary robotics. Artif Life 7:215–223

    Article  Google Scholar 

  37. Prokopenko M, Gerasimov V, Tanev I (2006) Evolving spatiotemporal coordinationin a modular robotic system. In: Rocha LM, Yaeger LS, Bedau MA, Floreano D, Goldstone RL, Vespignani A (eds) Artificial Life X: Proceedings of theTenth International Conference on the Simulation and Synthesis of Living Systems. MIT Press, Boston

    Google Scholar 

  38. Scassellati B (2001) Foundations for a Theory of Mind for a HumanoidRobot. Ph D thesis, Department of Electrical Engineering and Computer Science, MIT, Boston

    Google Scholar 

  39. Scheier C, Pfeifer R, Kunyioshi Y (1998) Embedded neural networks: exploitingconstraints. Neural Netw 11:1551–1596

    Article  Google Scholar 

  40. Schmitz A, Gómez G, Iida F, Pfeifer R (2007) On the robustness of simple speedcontrol for a quadruped robot. In: Proceeding of theInternational Conference on Morphological Computation, Venice, Italy

    Google Scholar 

  41. Slocum AC, Downey DC, Beer RD (2000) Further experiments in the evolution ofminimally cognitive behavior: From perceiving affordances to selective attention. In: Meyer J, Berthoz A, Floreano D, Roitblat H, Wilson S (eds) FromAnimals to Animats 6. Proceedings of the Sixth International Conference on Simulation of Adaptive Behavior. MIT Press,Cambridge

    Google Scholar 

  42. Schmidhuber J (2006) Developmental robotics, optimal artificial curiosity,creativity, music, and the fine arts. Connect Sci 18(2):173–187

    Article  Google Scholar 

  43. Steels L (2003) Evolving grounded communication for robots. Trends Cogn Sci7(7):308–312

    Article  Google Scholar 

  44. Sugita Y, Tani J (2005) Learning semantic combinatoriality from theinteraction between linguistic and behavioral processes. AdaptBehav 13(1):33–52

    Article  Google Scholar 

  45. Tani J, Fukumura N (1997) Self‐organizing internal representation inlearning of navigation: A physical experiment by the mobile robot Yamabico. Neural Netw 10(1):153–159

    Article  Google Scholar 

  46. Tani J, Nolfi S (1999) Learning to perceive the world as articulated: Anapproach for hierarchical learning in sensory‐motor systems. Neural Netw 12:1131–1141

    Article  Google Scholar 

  47. Tani J, Nishimoto R, Namikawa J, Ito M (2008) Co‐developmental learningbetween human and humanoid robot using a dynamic neural network model. IEEE Trans Syst Man Cybern B. Cybern 38:1

    Google Scholar 

  48. Varela FJ, Thompson E, Rosch E (1991) The Embodied mind: Cognitive science andhuman experience. MIT Press, Cambridge

    Google Scholar 

  49. van Gelder TJ (1998) The dynamical hypothesis in cognitive science. BehavBrain Sci 21:615–628

    Google Scholar 

  50. Vaughan E, Di Paolo EA, Harvey I (2004) The evolution of control andadaptation in a 3D powered passive dynamic walker. In: Pollack J, Bedau M, Husband P, Ikegami T, Watson R (eds) Proceedings of the NinthInternational Conference on the Simulation and Synthesis of Living Systems. MIT Press, Cambridge

    Google Scholar 

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Nolfi, S. (2012). Embodied and Situated Agents, Adaptive Behavior in. In: Meyers, R. (eds) Computational Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1800-9_60

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