Advanced search
SenseLab
SimToolDB
ModelDB Help
User account
Login
Register
Find models by
Model name
First author
Each author
Region(circuits)
Find models for
Cell type
Current
Receptor
Gene
Transmitters
Concept
Simulators
Methods
Find models of
Realistic Networks
Neurons
Electrical synapses (gap junctions)
Chemical synapses
Ion channels
Neuromuscular junctions
Axons
Pathophysiology
Other resources
SenseLab mailing list
ModelDB related resources
Computational neuroscience ecosystem
Models in a git repository
A reinforcement learning example (Sutton and Barto 1998)
Help downloading and running models
Model Information
Model File
Citations
Accession:
83514
This MATLAB script demonstrates an example of reinforcement learning functions guiding the movements of an agent (a black square) in a gridworld environment. See at the top of the matlab script and the book for more details.
References:
1 .
Sutton RS, Barto AG (2002)
Reinforcement learning: An introduction (2nd ed)
2 .
Sutton RS, Barto AG (1998)
Reinforcement learning: an introduction
Model Information
(Click on a link to find other models with that property)
Model Type:
Connectionist Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
MATLAB (web link to model);
Model Concept(s):
Reinforcement Learning;
Implementer(s):
Hasselmo, Michael E [hasselmo at bu.edu];
(located via links below)
Loading data, please wait...