Publications on Neuro-biological RL
Biased Random-Walk Learning: A Neurobiological Correlate to Trial-and-Error
Progress in Neural Networks
(Postscript - 248KB)
Neural network models offer a theoretical testbed for the study of
learning at the network level. ...
G.S. T.J. Sejnowski
A computational model of basal ganglia function with output selection
reinforcement learning, T.J.
Sejnowski Society for Neuroscience Abstracts, 20:2 (1994
We propose a computational model of the basal ganglia based closely on known anatomy and physiology....
, Russell W. Anderson
How the Brain Adjusts Synapses -- Maybe
Atomated Reasoning, Kluwer, NY (1991)
(Hardcopy Only - )
neurobiological learning ...
Gradient-Based Reinforcement Learning: Learning Combinations of Control Policies
Technical Report 97.50, Dip. Elettronica e Informazione, Politecnico di Milano
( gzipped Postscript - 381 KB)
This report presents two innovative model-based reinforcement
learning algorithms for continuous st...
Using a time-delay actor-critic neural architecture with dopamine-like reinforcement signal for learning in autonomous robots
Emerging Neural Architectures based on Neuroscience, S. Wermter, J. Austin, D. Willshaw (Eds.), Springer-verlag, LNAI 2036,
(PDF - 250 Kb)
Neuroscientists have identified a neural substrate of prediction and reward in experiments wi...
, Deffayet, C. and Sejnowski, T. J.
Reinforcement learning predicts the site of plasticity for auditory
remapping in the barn owl
In: G. Tesauro, D.
Alspector (Eds.) Advances in Neural Information Processing Systems 7,
MIT Press, Cambridge, MA, 125-132 (1995).
(no abstract available)...
, Yoshua Bengio, John Kalask
Brain Inspired Reinforcement Learning
NIPS 2004 (NIPS 17)
Successful application of reinforcement learning algorithms often involves considerable hand-craftin...
, Andrew Barto
Robot weightlifting by direct policy search
(PDF - 815KB)
This paper describes a method for structuring a robot motor learning task. By
designing a suitably ...
, Bernd Porr( email@example.com)
Temporal sequence learning, prediction and control - A review of different models and their relation to biological mechanisms
Neural Computation, 17: 245-319
A review of RL in view of its relation to classical conditioning and the biophysics of the underlyin...
, samuel delepoulle, jean-claude darcheville( firstname.lastname@example.org)
A Generic architecture for Adaptive Agents Based on Reinforcement Learning
Information Sciences Journal
In this paper, we present MAABAC, a generic model for building adaptive agents: they learn new behav...