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TSD
2010
Springer
15 years 1 months ago
A Priori and A Posteriori Machine Learning and Nonlinear Artificial Neural Networks
The main idea of a priori machine learning is to apply a machine learning method on a machine learning problem itself. We call it "a priori" because the processed data se...
Jan Zelinka, Jan Romportl, Ludek Müller
WRAC
2005
Springer
15 years 9 months ago
Distributed Agent Evolution with Dynamic Adaptation to Local Unexpected Scenarios
Abstract. This paper introduces a novel framework for designing multiagent systems, called “Distributed Agent Evolution with Dynamic Adaptation to Local Unexpected Scenarios” (...
Suranga Hettiarachchi, William M. Spears, Derek Gr...
150
Voted
AAMAS
2002
Springer
15 years 3 months ago
Relational Reinforcement Learning for Agents in Worlds with Objects
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
Saso Dzeroski
193
Voted
ATAL
2010
Springer
15 years 4 months ago
Role evolution in Open Multi-Agent Systems as an information source for trust
In Open Multi-Agent Systems (OMAS), deciding with whom to interact is a particularly difficult task for an agent, as repeated interactions with the same agents are scarce, and rep...
Ramón Hermoso, Holger Billhardt, Sascha Oss...
129
Voted
ICWL
2004
Springer
15 years 9 months ago
An Agent- and Service-Oriented e-Learning Platform
This paper presents an e-Learning Web-reachable hypermedia system as the foundation of a course content development toolset. Course content, developed in XML, is stored in native X...
Ivan Madjarov, Omar Boucelma, Abdelkader Bé...