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AI
1999
Springer
13 years 7 months ago
Learning by Discovering Concept Hierarchies
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...
GECCO
2005
Springer
189views Optimization» more  GECCO 2005»
14 years 1 months ago
Molecular programming: evolving genetic programs in a test tube
We present a molecular computing algorithm for evolving DNA-encoded genetic programs in a test tube. The use of synthetic DNA molecules combined with biochemical techniques for va...
Byoung-Tak Zhang, Ha-Young Jang
AAAI
1994
13 years 9 months ago
The Ups and Downs of Lexical Acquisition
We have implemented an incremental lexical acquisition mechanism that learns the meanings of previously unknown words from the context in which they appear, as a part of the proce...
Peter M. Hastings, Steven L. Lytinen
CP
2009
Springer
14 years 8 months ago
Constraint-Based Optimal Testing Using DNNF Graphs
The goal of testing is to distinguish between a number of hypotheses about a systemfor example, dierent diagnoses of faults by applying input patterns and verifying or falsifying t...
Anika Schumann, Martin Sachenbacher, Jinbo Huang
PKDD
2010
Springer
122views Data Mining» more  PKDD 2010»
13 years 6 months ago
Exploration in Relational Worlds
Abstract. One of the key problems in model-based reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large relational domains, in wh...
Tobias Lang, Marc Toussaint, Kristian Kersting