A reinforcement learning theory for homeostatic regulation

Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

Volumn , Issue , 2011, Pages

  Keramati, Mehdi ^a   Gutkin, Boris ^a  

^a ECOLE NORMALE SUPÉRIEURE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIORAL RESEARCH; FEEDBACK; PHYSIOLOGICAL MODELS; PHYSIOLOGY; REINFORCEMENT LEARNING;

BEHAVIORAL ADAPTATION; EXTERNAL ENVIRONMENTS; FEEDBACK MODEL; GOAL-DIRECTED; HOMEOSTATIC REGULATIONS; INTERNAL STATE; REDUCTION THEORY; REINFORCEMENT LEARNING MODELS; REINFORCEMENT LEARNING THEORIES; SETPOINTS;

ANIMALS;

EID: 85162538375     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. R. S. Sutton and A. G. Barto. Reinforcement Learning: An Introduction. MIT Press, Cambridge, 1998.
2. W. Schultz, P. Dayan, and P. R. Montague. A neural substrate of prediction and reward. Science, 275(5306):1593-1599, 1997.
3. F. M. Toates. Motivational Systems. Problems in the behavioral sciences. Cambridge University Press, New York, 1986.
4. J. E. R. Staddon. Adaptive behavior and learning. Cambridge University Press, New York, 1983.
5. K. C. Berridge. Motivation concepts in behavioral neuroscience. Physiol Behav, 81(2):179-209, 2004.
6. S.C.Woods and R.J. Seeley. Hunger and energy homeostasis. In C. R. Gallistel, editor, Volume 3 of Steven's Handbook of Experimental Psychology: Learning, Motivation, and Emotion, pages 633-68. Wiley, New York, third edition, 2002.
7. N. E. Miller and M. L. Kessen. Reward effects of food via stomach fistula compared with those of food via mouth. J Comp Physiol Psychol, 45(6):555-564, 1952.
8. C. L. Hull. Principles of behavior: an introduction to behavior theory. The Century psychology series. Appleton-Century-Crofts, New York, 1943.
9. P. Skjoldager, P. J. Pierre, and G. Mittleman. Reinforcer magnitude and progressive ratio responding in the rat: Effects of increased effort, prefeeding, and extinction. Learn motiv, 24(3):303-343, 1993.
10. W. Hodos. Progressive ratio as a measure of reward strength. Science, 134:943-944, 1961.
11. A. Dickinson and B. W. Balleine. The role of learning in motivation. In C. R. Gallistel, editor, Volume 3 of Steven's Handbook of Experimental Psychology: Learning, Motivation, and Emotion, pages 497-533. Wiley, New York, third edition, 2002.
12. George Konidaris and Andrew Barto. An adaptive robot motivational system. In Proceedings of the 9th international conference on Simulation of adaptive behavior : from animals to animats 9, pages 346-356, 2006.
13. N. D. Daw, Y. Niv, and P. Dayan. Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nat Neurosci, 8(12):1704-11, 2005.
14. Y. Niv, D. Joel, and P. Dayan. A normative perspective on motivation. Trends Cogn Sci, 10(8):375-381, 2006.
15. J. G. Mansfield, R. S. Benedict, and S. C. Woods. Response specificity of behaviorally augmented tolerance to ethanol supports a learning interpretation. Psychopharmacology, 79(2-3):94-98, 1983.
16. L. H. Schneider. Orosensory self-stimulation by sucrose involves brain dopaminergic mechanisms. Ann. N. Y. Acad. Sci, 575:307-319, 1989.
17. J. Zhang, K. C. Berridge, A. J. Tindell, K. S. Smith, and J.W. Aldridge. A neural computational model of incentive salience. PLoS Comp Biol, 5(7), 2009.
18. Hugues Bersini. Reinforcement learning for homeostatic endogenous variables. In Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3, page 325333, Brighton, United Kingdom, 1994. MIT Press. ACM ID: 189936.