Integrating neuroscience-based models towards an autonomous biomimetic Synthetic Forager

2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011

Volumn , Issue , 2011, Pages 210-215

  Rennó Costa, César ^b   Luvizotto, André L ^b   Marcos, Encarni ^b   Duff, Armin ^b   Sanchez Fibla, Marti ^b   Verschure, Paul F M J ^a,b  

^a INSTITUCIÓ CATALANA DE RECERCA I ESTUDIS AVANÇATS ICREA   (Spain)

^b UNIVERSITAT POMPEU FABRA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

AUTONOMOUS CONTROL; BEHAVIORAL CONTROL; BIO-MIMETIC CONTROL; COGNITIVE PROCESS; CONSTRAINED MODELS; COORDINATE COMPLEXES; DISTRIBUTED ADAPTIVE CONTROL; ENVIRONMENTAL CONDITIONS; EXPERIMENTAL PROTOCOLS; GOAL-ORIENTED; HIGH MOBILITY; MULTI-MODAL; NATURAL SYSTEMS; OPEN ENVIRONMENT; ROBOTIC PLATFORMS; ROBOTIC SYSTEMS; RULE LEARNING; SENSORY PROCESSING;

BEHAVIORAL RESEARCH; BIOMIMETICS; BRAIN MODELS; MAMMALS;

ROBOTICS;

EID: 84860706662     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBIO.2011.6181287     Document Type: Conference Paper

References (39)

1. J. B. Calhoun, The ecology and sociology of the Norway rat. U.S. Dept. of Health, Education, and Welfare, Public Health Service, 1963.
2. D. W. Stephens, J. S. Brown, and R. C. Ydenberg, Foraging: Behavior and Ecology. Chicago: University of Chicago Press, 2007.
3. S. Song and K. J. Waldron, Machines that walk: The adaptive suspension vehicle. Cambridge, MA: MIT Press, 1989.
4. H. Chen and C.-an Zhu, "Modeling the dynamics of biomimetic underwater robot fish," in IEEE International Conference on Robotics and Biomimetics, pp. 478-83, 2005.
5. Z. Mathews et al., "Insect-Like mapless navigation based on head direction cells and contextual learning using chemovisual sensors," in IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2243-50, 2009.
6. N. F. Lepora et al., "Naive Bayes novelty detection for a moving robot with whiskers," in IEEE International Conference on Robotics and Biomimetics, pp. 131-36, 2010.
7. Y. Jin and Y. Meng, "Morphogenetic Robotics: An Emerging New Field in Developmental Robotics," IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41(2), pp. 145-160, Mar. 2011.
8. J. S. MacDonall, J. Goodell, and A. Juliano, "Momentary maximizing and optimal foraging theories of performance on concurrent VR schedules.," Behavioural Processes, 72(3), pp. 283-299, 2006.
9. H. Davis, "Underestimating the rat's intelligence.," Brain research. Cognitive brain research, 3(3-4), pp. 291-8, 1996.
10. R. J. Herrnstein, "On the law of effect.," Journal of the experimental analysis of behavior, 13(2), pp. 243-66, 1970.
11. W. A. Roberts, "Foraging by rats on a radial maze:Learning, memory, and decision rules," in Learning and memory: The behavioral and biological substrates, I. Gormezano and E. Wasserman, Eds. Hillsdale, NJ: Erlbaum, pp. 7-24, 1992.
12. L.-A. Giraldeau and T. Caraco, Social Foraging Theory. Princeton University Press, pp. 376, 2000.
13. P. F. M. J. Verschure, B. Kröse, and R. Pfeifer, "Distributed Adaptive Control: The self-organization of structured behavior," Robotics and Autonomous Systems, 9, pp. 181-96, 1992.
14. K. Eng et al., "Ada - intelligent space: an artificial creature for the SwissExpo.02," in IEEE International Conference on Robotics and Automation, 3, pp. 4154-59, 2003.
15. J. Manzolli and P. F. M. J. Verschure, "Roboser: A Real-World Composition System," Computer Music Journal, 29(3), pp. 55-74, 2005.
16. P. F. M. J. Verschure, T. Voegtlin, and R. J. Douglas, "Environmentally mediated synergy between perception and behaviour in mobile robots," Nature, 425, pp. 620-24, 2003.
17. M. Sanchez-Fibla et al., "Allostatic Control for Robot Behavior Regulation: a Comparative Rodent-Robot Study,"Advances in Complex Systems, 13(3), pp. 377, 2010.
18. A. Duff and P. F. M. J. Verschure, "Unifying perceptual and behavioral learning with a correlative subspace learning rule, "Neurocomputing, 73(10-12), pp. 1818-30, 2010.
19. R. Wyss, P. Konig, and P. F. M. J. Verschure, "Invariant representations of visual patterns in a temporal population code.," Proceedings of the National Academy of Sciences of the United States of America, 100(1), pp. 324-9, 2003.
20. P. F. M. J. Verschure, R. Wyss, and P. König, "A Model of the Ventral Visual System Based on Temporal Stability and Local Memory," PLOS Biology, 4(5), pp. 1-8, 2006.
21. A. Duff, M. Sanchez Fibla, and P. F. M. J. Verschure, "A biologically based model for the integration of sensory-motor contingencies in rules and plans: A prefrontal cortex based extension of the Distributed Adaptive Control architecture.,"Brain research bulletin, 85(5), pp. 289-304, 2011.
22. P. F. M. J. Verschure and P. Althaus, "A real-world rational agent: unifying old and new AI," Cognitive Science, 27(4), pp. 30, 2003.
23. D. G. Lowe, "Object recognition from local scale-invariant features," in IEEE International Conference on Computer Vision, 2, pp. 1150-57, 1999.
24. J. E. Lisman, "Role of the dual entorhinal inputs to hippocampus: a hypothesis based on cue/action (non-self/self) couplets," in Progress in brain research, 163, pp 615-25, 2007.
25. S. Leutgeb and J. K. Leutgeb, "Pattern separation, pattern completion, and new neuronal codes within a continuous CA3 map.," Learning & memory, 14(11), pp. 745-57, 2007.
26. L. de Almeida, M. Idiart, and J. E. Lisman, "A second function of gamma frequency oscillations: an E%-max winner-take-all mechanism selects which cells fire.," The Journal of Neuroscience, 29(23), pp. 7497-503, 2009.
27. L. de Almeida, M. Idiart, and J. E. Lisman, "The input-output transformation of the hippocampal granule cells: from grid cells to place fields.," The Journal of Neuroscience, 29(23), pp. 7504-12, 2009.
28. C. Rennó-Costa, J. E. Lisman, and P. F. M. J. Verschure, "The mechanism of rate remapping in the dentate gyrus.," Neuron, 68(6), pp. 1051-8, 2010.
29. A. Guanella and P. Verschure, "A Model of Grid Cells Based on a Path Integration Mechanism," in Artificial Neural Networks - ICANN 2006, 4131/2006, S. D. Kollias, A. Stafylopatis, W. Duch, and E. Oja, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 740-749. 2006.
30. E. Marcos, A. Duff, M. Sanchez-Fibla, and P. F. M. J. Verschure, "The neuronal substrate underlying order and interval representations in sequential tasks: A biologically based robot study," in IEEE/IJCNN International Joint Conference on Neural Networks, pp. 1-8, 2010.
31. J. O'Keefe and J. Dostrovsky, "The hippocampus as a spatial map. Preliminary evidence from unit activity in the freelymoving rat.," Brain research, 34(1), pp. 171-5, 1971.
32. A. Guanella and P. F. M. J. Verschure, "Prediction of the position of an animal based on populations of grid and place cells: a comparative simulation study.," Journal of integrative neuroscience, 6(3), pp. 433-46, 2007.
33. J. K. Leutgeb, S. Leutgeb, M.-B. Moser, and E. I. Moser, "Pattern separation in the dentate gyrus and CA3 of the hippocampus.," Science, 315(5814), pp. 961-966, 2007.
34. W. E. Skaggs, B. L. McNaughton, K. M. Gothard, and E. J. Markus, "An Information-Theoretic Approach to Deciphering the Hippocampal Code," in In Advances in Neural Information Processing Systems, 5, pp. 1030-1037, 1993.
35. J. P. Aggleton, M. M. Albasser, D. J. Aggleton, G. L. Poirier, and J. M. Pearce, "Lesions of the rat perirhinal cortex spare the acquisition of a complex configural visual discrimination yet impair object recognition.," Behavioral neuroscience, 124(1), pp. 55-68, 2010.
36. U. Bernardet, S. B. i Badia, and P. F. M. J. Verschure, "The eXperience Induction Machine and its Role in the Research on Presence," in The 10th Annual International Workshop on Presence, 2007.
37. M. E. Walton, D. M. Bannerman, and M. F. S. Rushworth, "The Role of Rat Medial Frontal Cortex in Effort-Based Decision Making," J. Neurosci., 22(24), pp. 10996-1003, 2002.
38. J. J. Leonard and H. F. Durrant-Whyte, "Simultaneous map building and localization for an autonomous mobile robot," in IEEE/RSJ International Workshop on Intelligent Robots and Systems, pp. 1442-1447, 1991.
39. A. Duff et al., From Motor Learning to Interaction Learning in Robots, 264. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 15-41, 2010.