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ECAI
2004
Springer
14 years 2 months ago
A Backtracking Strategy for Order-Independent Incremental Learning
Agents that exist in an environment that changes over time, and are able to take into account the temporal nature of experience, are commonly called incremental learners. It is wid...
Nicola Di Mauro, Floriana Esposito, Stefano Ferill...
ILP
2000
Springer
14 years 27 days ago
Using ILP to Improve Planning in Hierarchical Reinforcement Learning
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...
Mark D. Reid, Malcolm R. K. Ryan
AOIS
2004
13 years 10 months ago
A Systematic Approach for Including Machine Learning in Multi-agent Systems
Large scale multi-agent systems (MASs) in unpredictable environments must use machine learning techniques to perform their goals and improve the performance of the system. This pap...
José Alberto R. P. Sardinha, Alessandro F. ...
CEC
2005
IEEE
14 years 2 months ago
Evolving improved incremental learning schemes for neural network systems
It is well known that incremental learning can often be difficult for traditional neural network systems, due to newly learned information interfering with previously learned infor...
Tebogo Seipone, John A. Bullinaria
CEC
2009
IEEE
14 years 4 months ago
Hyper-learning for population-based incremental learning in dynamic environments
— The population-based incremental learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning. Recently, the PBIL algorithm has been applied...
Shengxiang Yang, Hendrik Richter