Reinforcement learning and time perception - A model of animal experiments

Advances in Neural Information Processing Systems

Volumn , Issue , 2002, Pages

  Shapiro, J L ^a   Wearden, John ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

REINFORCEMENT LEARNING;

ANIMAL EXPERIMENTS; SCALAR PROPERTIES; SIMPLE MODELING; SINGLE CURVES; SPIKING NEURON; THREE PARAMETERS; TIME INTERVAL; TIME PERCEPTION;

EXPERIMENTS;

EID: 84899030341     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. M. Abramowitz and I. A. Stegun, editors. Handbook of Mathematical Functions. New York: Dover Publications, 1967.
2. Russell M. Church, Walter H. Meek, and John Gibbon. Application of scalar timing theory to individual trials. Journal of Experimental Psychology - Animal Behavior Processes, 20(2):135-155, 1994.
3. John Gibbon and Russell M. Church. Representation of time. Cognition, 37:23-54, 1990.
4. Stephen Grossberg and John W. L. Merrill. A neural network model of adaptively timed reinforcement learning and hippocampal dynamics. Cognitive Brain Research, 1:3-38, 1992.
5. S. C. Hinton and W. H. Meek. How time flies: Functional and neural mechansims of interval timing. In C. M. Bradshaw and E. Szadabi, editors, Time and Behaviour: Psychological and Neurobehavioural Analyses. Amsterdam: Elsevier Science, 1997.
6. J. W. Moore, J. E. Desmond, and N. E. Berthier. Adaptively timed conditioned responses and the cerebellum: A neural network approach. Biological Cybernetics, 62:17-28, 1989.
7. John W. Moore, Neil D. Berthier, and Diana E. J. Blazis. Classical eye-blink conditioning: Brain systems and implementation of a computational model. In Michael Gabriel and John Moore, editors, Learning and Computational Neuroscience: Foundations of Adaptive Networks, A Bradford Book, pages 359-387. The MIT Press, 1990.
8. J. L. Shapiro and John Wearden. Modelling scalar timing by an accumulator network of spiking neurons. In preparation, 2001.
9. Richard S. Sutton and Andrew G. Barto. Reinforcment Learning: An Introduction. A Bradford Book. The MIT Press, 1998.