Contribution to the study and the design of reinforcement functions

  • Juan Miguel Santos Universidad de Buenos Aires

Resumen

The underlying concept in Reinforcement Learning is as simple as it is attractive: to learn by trial and error from the interaction with the environment. This approach allows us to deal with problems where a learning technique searches to improve the performance of the agent (the learner) over time. Reinforcement Learning groups a set of such techniques, and it uses a performance measure based on two types of signals given by a Critic or Reinforcement Function: penalty and reward.

Publicado
2000-10-19
Cómo citar
Santos, J. M. (2000). Contribution to the study and the design of reinforcement functions. Electronic Journal of SADIO (EJS), 3(1). Recuperado a partir de https://ojs.sadio.org.ar/index.php/EJS/article/view/127