Sentence examples for temporal learning from inspiring English sources

Importantly, these relatively fast timescales match the temporal learning windows of neurons (<50 ms) [56], and hence, may render spike-timing dependent synaptic plasticity operant for learning informative activation patterns.

The protocol used in the I-ELCAP research was reviewed semi-annually and modified over time and with increasing experience in the analysis of the study data, which likely impacted the volume of procedures indicated in years subsequent to the baseline year because of a temporal, learning effect.

The possible neural basis of temporal learning generalization is discussed.

This form of temporal learning underlies the ability of the networks to learn temporal sequences of behaviour.

Individual learning refers to trial and error, or insight temporal learning, and social learning refers to spatial leaning through interactions with other individuals.

Secondly, learning of temporal structures was found during reproduction of sequential stimuli with random ordinal structure, suggesting independent mechanisms for temporal learning.

Using a learning transfer design, we found evidence for independent temporal representations: learning a spatiotemporal sequence facilitated learning its temporal and ordinal structure alone; learning a temporal and an ordinal structure facilitated learning of a sequence where the two were coupled.

In 1995, an IBM academic, Gerald Tesauro, presented the "temporal difference learning technique", and the resultant neural network backgammon software TD-Gammon.

A number of computational models have explained the behavior of dopamine neurons in terms of temporal difference learning.

The developed control system is embedded with a trust evaluation model, designed using a novel adaptation of Markov Games concept into temporal difference learning to compute the direct trust and using a novel heuristic method to integrate the indirect trust.

The component-level PM policy is pre-specified and fixed whereas the system-level PM employs temporal difference learning on semi-Markov decision process as the model-free RL technique, and it is specifically optimized for a heterogeneous application pool.