Andrew G. Barto

Toward a modern theory of adaptive networks: Expectation and prediction.

Many adaptive neural network theories are based on neuronlike adaptive elements that can behave as single unit analogs of associative conditioning. In this article we develop a ...

A Model of How the Basal Ganglia Generate and Use Neural Signals That Predict Reinforcement

This chapter contains sections titled: Introduction, Dopamine Neurons, Organization of Strtosomal Modules, Mechanism of Responsiveness to Predictors of Reinforcement, Correspond...

On the Computational Economics of Reinforcement Learning

Improving Elevator Performance Using Reinforcement Learning

This paper describes the application of reinforcement learning (RL) to the difficult real world problem of elevator dispatching. The elevator domain poses a combination of chall...

Associative search network: A reinforcement learning associative memory