4544 search results - page 11 / 909 » Reinforcement Learning with Time |
SYNASC
2005
IEEE
14 years 1 months ago
2005
IEEE
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
ICRA
2005
IEEE
14 years 1 months ago
2005
IEEE
— This paper presents a new reinforcement learning algorithm for accelerating acquisition of new skills by real mobile robots, without requiring simulation. It speeds up Q-learni...
EVOW
2003
Springer
14 years 21 days ago
2003
Springer
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
ICANN
2001
Springer
13 years 12 months ago
2001
Springer
Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
AIPS
2006
13 years 9 months ago
2006
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...