748 search results - page 22 / 150 » A Reinforcement Learning Algorithm for Spiking Neural Networ... |
ICANN
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. Developing superior artificial board-game players is a widelystudied area of Artificial Intelligence. Among the most challenging games is the Asian game of Go, which, des...
AI
2002
Springer
13 years 7 months ago
2002
Springer
TD-Gammon is a neural network that is able to teach itself to play backgammon solely by playing against itself and learning from the results. Starting from random initial play, TD...
ICANN
2003
Springer
14 years 16 days ago
2003
Springer
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabili...
NN
2002
Springer
13 years 7 months ago
2002
Springer
In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
NN
2007
Springer
13 years 6 months ago
2007
Springer
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...