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ICML
2009
IEEE
16 years 1 months ago
Active learning for directed exploration of complex systems
Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fid...
Michael C. Burl, Esther Wang
NCA
2007
IEEE
16 years 21 days ago
Implementing Atomic Data through Indirect Learning in Dynamic Networks
Developing middleware services for dynamic distributed systems, e.g., ad-hoc networks, is a challenging task given that such services deal with dynamically changing membership and...
Kishori M. Konwar, Peter M. Musial, Nicolas C. Nic...
ATAL
2003
Springer
15 years 11 months ago
Coordination in multiagent reinforcement learning: a Bayesian approach
Much emphasis in multiagent reinforcement learning (MARL) research is placed on ensuring that MARL algorithms (eventually) converge to desirable equilibria. As in standard reinfor...
Georgios Chalkiadakis, Craig Boutilier
CEEMAS
2003
Springer
15 years 11 months ago
On a Dynamical Analysis of Reinforcement Learning in Games: Emergence of Occam's Razor
Modeling learning agents in the context of Multi-agent Systems requires an adequate understanding of their dynamic behaviour. Usually, these agents are modeled similar to the di...
Karl Tuyls, Katja Verbeeck, Sam Maes
ICML
2000
IEEE
15 years 10 months ago
Using Learning by Discovery to Segment Remotely Sensed Images
In this paper, we describe our research in computer-aided image analysis. We have incorporated machine learning methodologies with traditional image processing to perform unsuperv...
Leen-Kiat Soh, Costas Tsatsoulis