Sentence examples for reinforcement principles from inspiring English sources

Established roadway roof reinforcement principles can potentially be applied to coal pillar design under this representation.

A social skills plus relaxation training (SSRT) program was developed using direct training, relaxation training, and reinforcement principles.

Additionally, the report asks sites to consider whether their self-designed CM protocol: 1) emphasizes core positive reinforcement principles; 2) gives offenders early rewards; and 3) requires any changes before they begin protocol implementation.

However, connectionist models also show that network organisations sufficient for many collective behaviours can be generated via learning mechanisms that modify the strength of connections according to only very simple and local reinforcement principles – even by mechanisms that do not require any system-level reward or performance-based feedback.

In the next section, we will describe the mutual reinforcement principle [1] that underlies MUSE.

Next, we exploit this mutual reinforcement principle in the bipartite graph network to simultaneously estimate the reputation and the risk using the propagation algorithm described in the next section.

Instead of considering a risk as an isolated and static property pertaining only to individual users or devices, MUSE exploits a novel mutual reinforcement principle and models the dynamics of risk based on the interdependent relationship among multiple entities.

The suggested Immune Network Algorithm based Multi-Agent System (INAMAS) provides intelligent mechanisms that capture disturbance-related knowledge explicitly and take advantage of previous successes and failures in dealing with disturbances through an adaptation of the reinforcement principle.

In the case of head-butting for the last fallen Tootsie Roll, there's a reinforcement principle operating.

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.