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» Learning Bounds for Domain Adaptation
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KI
2002
Springer
13 years 9 months ago
Advantages, Opportunities and Limits of Empirical Evaluations: Evaluating Adaptive Systems
While empirical evaluations are a common research method in some areas of Artificial Intelligence (AI), others still neglect this approach. This article outlines both the opportun...
Stephan Weibelzahl, Gerhard Weber
TMI
2002
248views more  TMI 2002»
13 years 9 months ago
Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming
This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Alain Pitiot, Arthur W. Toga, Paul M. Thompson
AAMAS
2007
Springer
13 years 10 months ago
A framework for meta-level control in multi-agent systems
Sophisticated agents operating in open environments must make decisions that efficiently trade off the use of their limited resources between dynamic deliberative actions and dom...
Anita Raja, Victor R. Lesser
ATAL
2010
Springer
13 years 11 months ago
Frequency adjusted multi-agent Q-learning
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Michael Kaisers, Karl Tuyls
CONNECTION
2008
178views more  CONNECTION 2008»
13 years 10 months ago
Spoken language interaction with model uncertainty: an adaptive human-robot interaction system
Spoken language is one of the most intuitive forms of interaction between humans and agents. Unfortunately, agents that interact with people using natural language often experienc...
Finale Doshi, Nicholas Roy