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ATAL
2007
Springer
16 years 29 days ago
IFSA: incremental feature-set augmentation for reinforcement learning tasks
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...
Mazda Ahmadi, Matthew E. Taylor, Peter Stone
IJCAI
2007
15 years 8 months ago
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL
The goal of transfer learning is to use the knowledge acquired in a set of source tasks to improve performance in a related but previously unseen target task. In this paper, we pr...
Manu Sharma, Michael P. Holmes, Juan Carlos Santam...
ATAL
2007
Springer
15 years 10 months ago
Hypotheses refinement under topological communication constraints
We investigate the properties of a multiagent system where each (distributed) agent locally perceives its environment. Upon perception of an unexpected event, each agent locally c...
Gauvain Bourgne, Gael Hette, Nicolas Maudet, Suzan...
ATAL
2005
Springer
16 years 9 days ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
AAMAS
2004
Springer
15 years 6 months ago
Automated Assistants for Analyzing Team Behaviors
Multi-agent teamwork is critical in a large number of agent applications, including training, education, virtual enterprises and collective robotics. The complex interactions of ag...
Ranjit Nair, Milind Tambe, Stacy Marsella, Taylor ...