<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In this article, a new class of the epoch-incremental reinforcement learning algorithm is proposed. In the incremental mode, the fundamental TD(0) or TD(λ) algorithm is performed and an environment model is created. In the epoch mode, on the basis of the environment model, the distances of past-active states to the terminal state are computed. These distances and the reinforcement terminal state signal are used to improve the agent policy.</p></abstract>

In this article, a new class of the epoch-incremental reinforcement learning algorithm is proposed. In the incremental mode, the fundamental TD(0) or TD(λ) algorithm is performed and an environment model is created. In the epoch mode, on the basis of the environment model, the distances of past-active states to the terminal state are computed. These distances and the reinforcement terminal state signal are used to improve the agent policy.

Epoch-incremental reinforcement learning algorithms

Faculty of Electrical and Computer Engineering Rzeszów University of Technology, Al. Powstańców Warszawy 12, 35-959 Rzeszów, Poland

International Journal of Applied Mathematics and Computer Science

{"article-title":"Epoch-incremental reinforcement learning algorithms"}

In this article, a new class of the epoch-incremental reinforcement learning algorithm is proposed. In the incremental mode, the fundamental TD(0) or TD(λ)...

Epoch-incremental reinforcement learning algorithms

Publié en ligne: 30 sept. 2013

Pages: 623 - 635

DOI: https://doi.org/10.2478/amcs-2013-0047

This content is open access.