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HEURISTICS
2008
170views more  HEURISTICS 2008»
15 years 6 months ago
Accelerating autonomous learning by using heuristic selection of actions
This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control po...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
ICML
2003
IEEE
16 years 6 months ago
Q-Decomposition for Reinforcement Learning Agents
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...
Stuart J. Russell, Andrew Zimdars
CLIMA
2004
15 years 7 months ago
Learning in BDI Multi-agent Systems
Abstract. This paper deals with the issue of learning in multi-agent systems (MAS). Particularly, we are interested in BDI (Belief, Desire, Intention) agents. Despite the relevance...
Alejandro Guerra-Hernández, Amal El Fallah-...
203
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PAMI
2011
15 years 28 days ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
IDEAS
2003
IEEE
76views Database» more  IDEAS 2003»
15 years 11 months ago
E-Learning as a Web Service
E-learning platforms and their functionalities resemble one another to a large extend. Recent standardization efforts in e-learning concentrate on the reuse of learning material, ...
Gottfried Vossen, Peter Westerkamp