Sentence examples for by applying reinforcement learning from inspiring English sources

The policy path in a topic or story graph model is defined by applying reinforcement learning principles on dynamically defined event models associated with evolution of topic definition observed from incrementally acquired samples of input training data spanning multiple time windows.

The policy path in a topic or story graph model has been defined by applying reinforcement learning principles [26] on dynamically defined event models associated with evolution of topic definition observed from incrementally acquired samples of input training data spanning multiple time windows.

Actually, the overview of applying reinforcement learning to a cognitive wireless sensor network is illustrated in Fig. 1 in Section 1.

Khan and Rinner [8] apply reinforcement learning (RL) for online task scheduling.

In this article, we apply reinforcement learning (RL) algorithms to reduce the latency of AMI communications in LPWANs.

Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoner's Dilemma and Hawk-Dove games.

By applying computational reinforcement learning models to subjects' discrimination performance, the apparent enhanced sensitivity to misleading reinforcement described in the present study can be accounted for, somewhat counterintuitively, in terms of an overall reduction in reinforcement sensitivity.

To improve the neighbor prediction accuracy, we adaptively adjust the time windows by applying the reinforcement learning mechanism from the beginning of the whole procedure.

This paper approaches the syntactic alignment of a robot team by means of dialogic language games and by applying online probabilistic reinforcement learning algorithms.

Khan and Rinner [9] apply cooperative reinforcement learning (CRL) for online task scheduling.

7 The notion of the model as applied to reinforcement learning is understood as an internal map of events and stimuli from the external world.