Quantitative data on the speed with which animals acquire behavioral responses during classical conditioning experiments should provide strong constraints on models of learning. However, most models have simply ignored these data; the few that have attempted to address them have failed by at least an order of magnitude. We discuss key data on the speed of acquisition, and show how to account for them using a statistically sound model of learning, in which differential reliabilities of stimuli play a crucial role.
This dissertation focuses on the biological structures that allow animals to exhibit classical condi...
Learning to make rewarding choices in response to stimuli depends on a slow but steady process, rein...
This chapter presents a model of classical conditioning called the temporaldifference (TD) model. Th...
Quantitative data on the speed with which animals acquire behav- ioral responses during classical co...
C. R. Gallistel and J. Gibbon (2000) presented quantitative data on the speed with which animals acq...
Understanding how an animal’s ability to learn relates to neural activity or is altered by lesions, ...
C. R. Gallistel and J. Gibbon (2000) presented quantitative data on the speed with which animals acq...
Learning is fundamental to animal survival. Animals must learn to link sensory cues in the environme...
AbstractIn the perceptual learning (PL) literature, researchers typically focus on improvements in a...
Humans can learn associations between visual stimuli and motor responses from just a single instruct...
We present a computational model of movement skill learning. The types of skills addressed are a cla...
We describe computer simulation of a number of associative models of classical conditioning in an at...
Selective attention involves the differential processing of different stimuli, and has widespread ps...
Selective information processing in neural networks is studied through computer simulations of Pavlo...
Intelligent agents balance speed of responding with accuracy of deciding. Stochastic accumulator mod...
This dissertation focuses on the biological structures that allow animals to exhibit classical condi...
Learning to make rewarding choices in response to stimuli depends on a slow but steady process, rein...
This chapter presents a model of classical conditioning called the temporaldifference (TD) model. Th...
Quantitative data on the speed with which animals acquire behav- ioral responses during classical co...
C. R. Gallistel and J. Gibbon (2000) presented quantitative data on the speed with which animals acq...
Understanding how an animal’s ability to learn relates to neural activity or is altered by lesions, ...
C. R. Gallistel and J. Gibbon (2000) presented quantitative data on the speed with which animals acq...
Learning is fundamental to animal survival. Animals must learn to link sensory cues in the environme...
AbstractIn the perceptual learning (PL) literature, researchers typically focus on improvements in a...
Humans can learn associations between visual stimuli and motor responses from just a single instruct...
We present a computational model of movement skill learning. The types of skills addressed are a cla...
We describe computer simulation of a number of associative models of classical conditioning in an at...
Selective attention involves the differential processing of different stimuli, and has widespread ps...
Selective information processing in neural networks is studied through computer simulations of Pavlo...
Intelligent agents balance speed of responding with accuracy of deciding. Stochastic accumulator mod...
This dissertation focuses on the biological structures that allow animals to exhibit classical condi...
Learning to make rewarding choices in response to stimuli depends on a slow but steady process, rein...
This chapter presents a model of classical conditioning called the temporaldifference (TD) model. Th...