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EXACT
2009
13 years 7 months ago
Explaining a Result to the End-User: A Geometric Approach for Classification Problems
This paper addresses the issue of the explanation of the result given to the end-user by a classifier, when it is used as a decision support system. We consider machine learning cl...
Isabelle Alvarez, Sophie Martin
AAAI
1994
13 years 11 months ago
Solution Reuse in Dynamic Constraint Satisfaction Problems
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Gérard Verfaillie, Thomas Schiex
GECCO
2007
Springer
293views Optimization» more  GECCO 2007»
14 years 4 months ago
Solving the artificial ant on the Santa Fe trail problem in 20, 696 fitness evaluations
In this paper, we provide an algorithm that systematically considers all small trees in the search space of genetic programming. These small trees are used to generate useful subr...
Steffen Christensen, Franz Oppacher
ICML
1998
IEEE
14 years 10 months ago
RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
Malcolm R. K. Ryan, Mark D. Pendrith
GPEM
2008
128views more  GPEM 2008»
13 years 10 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood