ALLOSTATIC CONTROL FOR ROBOT BEHAVIOR REGULATION: A COMPARATIVE RODENT-ROBOT STUDY

Marti Sanchez-Fibla (), Ulysses Bernardet (), Erez Wasserman (), Tatiana Pelc (), Matti Mintz (), Jadin C. Jackson (), Carien Lansink (), Cyriel Pennartz () and Paul F. M. J. Verschure ()
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Marti Sanchez-Fibla: Laboratory for Synthetic Perceptive, Emotive and Cognitive Systems (SPECS), Universitat Pompeu Fabra, Carrer de Roc Boronat 138, E-08018, Barcelona, Spain
Ulysses Bernardet: Laboratory for Synthetic Perceptive, Emotive and Cognitive Systems (SPECS), Universitat Pompeu Fabra, Carrer de Roc Boronat 138, E-08018, Barcelona, Spain
Erez Wasserman: Psycho-biology Research Unit, Tel Aviv University, Tel Aviv, Israel
Tatiana Pelc: Psycho-biology Research Unit, Tel Aviv University, Tel Aviv, Israel
Matti Mintz: Psycho-biology Research Unit, Tel Aviv University, Tel Aviv, Israel
Jadin C. Jackson: SILS Swammerdam Institute for Life Sciences, University Van Amsterdam, Amsterdam, Holland
Carien Lansink: University of Maryland, MD, U.S.A.
Cyriel Pennartz: SILS Swammerdam Institute for Life Sciences, University Van Amsterdam, Amsterdam, Holland
Paul F. M. J. Verschure: SPECS, IUA, Universitat Pompeu Fabra, Carrer de Roc Boronat 138, E-08018, Barcelona, Spain;

Advances in Complex Systems (ACS), 2010, vol. 13, issue 03, 377-403

Abstract: Rodents are optimal real-world foragers that regulate internal states maintaining a dynamic stability with their surroundings. How these internal drive based behaviors are regulated remains unclear. Based on the physiological notion ofallostasis, we investigate a minimal control system able to approximate their behavior.Allostasisis the process of achieving stability with the environment through change, opposed to homeostasis which achieves it through constancy. Following this principle, the so-called allostatic control system orchestrates the interaction of the homeostatic modules by changing their desired values in order to achieve stability. We use a minimal number of subsystems and estimate the model parameters from rat behavioral data in three experimental setups: free exploration, presence of reward, delivery of cues with reward predictive value. From this analysis, we show that a rat is influenced by the shape of the arena in terms of its openness. We then use the estimated model configurations to control a simulated and real robot which captures essential properties of the observed rat behavior. The allostatic reactive control model is proposed as an augmentation of the Distributed Adaptive Control architecture and provides a further contribution towards the realization of an artificial rodent.

Keywords: Homeostasis; allostasis; rodent behavior; behavioral-based robotics (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:13:y:2010:i:03:n:s0219525910002621

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DOI: 10.1142/S0219525910002621

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