Sentence examples for model of reinforcement from inspiring English sources

Open image in new window Fig. 10 Seckin model of reinforcement hysteretic response (Wong and Vecchio 2003).

An effective numerical method is proposed in this paper to generate a meso-scale composite model of reinforcement concrete (RC) which contains aggregates with random size and shape based on Voronoi tessellation method.

Qualitatively similar results were presented by Servedio [13] for a mainland-island model of reinforcement where postzygotic isolation is caused by nuclear epistatic interactions.

These two hypotheses are separable and produce separable predictions, but together they form a coherent and parsimonious description of a multi-micro-agent (µAgent) TD model of reinforcement learning that provides a good fit to the experimental data.

A single-locus model of reinforcement of genetic coherence previously suggested by the present authors ([ 7]) allowed for a complete analysis covering a much wider range of mating systems.

The dopamine responses match this temporal profile of TD error closely, demonstrating the most complete relationship of phasic dopamine responses to the TD model of reinforcement so far reported.

Computational models of reinforcement learning (RL) strive to produce behavior that maximises reward, and thus allow software or robots to behave adaptively [1].

It is suggested that dopaminergic neurons provide a prediction error akin to the error computed in the temporal difference learning (TDL) models of reinforcement learning (RL).

Temporal-difference (TD) algorithms have been proposed as models of reinforcement learning (RL).

In this paper, we explored distributing two parameters of temporal difference (TD) models of reinforcement learning (RL): distributed discounting and distributed representations of belief.

In computational models of reinforcement learning, loss frequency affects action selection [ 60].