171 search results - page 12 / 35 » Principled Methods for Advising Reinforcement Learning Agent... |
TSMC
2002
13 years 7 months ago
2002
By using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rules for unseen situations. These benefits would be ...
NIPS
1997
13 years 9 months ago
1997
Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent’s limited computational resources to achieve a good estimate of the value of ...
ICCBR
2009
Springer
14 years 2 months ago
2009
Springer
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and ...
JCP
2008
13 years 7 months ago
2008
In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
ICML
1997
IEEE
14 years 8 months ago
1997
IEEE
Explanation-Based Reinforcement Learning (EBRL) was introduced by Dietterich and Flann as a way of combining the ability of Reinforcement Learning (RL) to learn optimal plans with...