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157
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ML
1998
ACM
136views Machine Learning» more  ML 1998»
15 years 5 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
170
Voted
ACL
2010
15 years 4 months ago
Fine-Grained Genre Classification Using Structural Learning Algorithms
Prior use of machine learning in genre classification used a list of labels as classification categories. However, genre classes are often organised into hierarchies, e.g., coveri...
Zhili Wu, Katja Markert, Serge Sharoff
EDM
2009
286views Data Mining» more  EDM 2009»
15 years 3 months ago
Does Self-Discipline impact students' knowledge and learning?
In this study, we are interested to see the impact of self-discipline on students' knowledge and learning. Self-discipline can influence both learning rate as well as knowledg...
Yue Gong, Dovan Rai, Joseph Beck, Neil T. Hefferna...
238
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Publication
154views
14 years 8 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
ICML
1996
IEEE
16 years 7 months ago
On the Learnability of the Uncomputable
Within Valiant'smodel of learning as formalized by Kearns, we show that computable total predicates for two formallyuncomputable problems the classical Halting Problem, and t...
Richard H. Lathrop