171 search results - page 12 / 35 » Principled Methods for Advising Reinforcement Learning Agent... |
TSMC
2002
15 years 2 days 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 ...
91
Voted
NIPS
1997
15 years 1 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 ...
134
Voted
ICCBR
2009
Springer
15 years 7 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 ...
102
Voted
JCP
2008
15 years 13 days 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
16 years 1 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...