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AIPS
2008
15 years 9 months ago
Learning Heuristic Functions through Approximate Linear Programming
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...
Marek Petrik, Shlomo Zilberstein
EDM
2010
185views Data Mining» more  EDM 2010»
15 years 8 months ago
Analysis of Productive Learning Behaviors in a Structured Inquiry Cycle Using Hidden Markov Models
This paper demonstrates the generality of the hidden Markov model approach for exploratory sequence analysis by applying the methodology to study students' learning behaviors ...
Hogyeong Jeong, Gautam Biswas, Julie Johnson, Larr...
CVPR
2004
IEEE
16 years 8 months ago
A Discriminative Learning Framework with Pairwise Constraints for Video Object Classification
In video object classification, insufficient labeled data may at times be easily augmented with pairwise constraints on sample points, i.e, whether they are in the same class or n...
Rong Yan, Jian Zhang, Jie Yang, Alexander G. Haupt...
196
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GECCO
2010
Springer
212views Optimization» more  GECCO 2010»
15 years 11 months ago
Generative and developmental systems
This paper argues that multiagent learning is a potential “killer application” for generative and developmental systems (GDS) because key challenges in learning to coordinate ...
Kenneth O. Stanley
ECTEL
2007
Springer
16 years 27 days ago
CAMEL: Taking the Technology Enhanced Learning Journey without Reinventing the Wheel
Projects involving technology are notoriously dogged with difficulties and a number of lessons can be learned. Rather than detail examples from particular TEL projects, the author ...
Gill Ferrell