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ICMLA
2009
13 years 6 months ago
Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapu...
COOPIS
2004
IEEE
14 years 14 days ago
Semantic Web Based Content Enrichment and Knowledge Reuse in E-science
We address the life cycle of semantic web based knowledge management from ontology modelling to instance generation and reuse. We illustrate through a semantic web based knowledge ...
Feng Tao, Liming Chen, Nigel Shadbolt, Fenglian Xu...
ATAL
2010
Springer
13 years 9 months ago
PAC-MDP learning with knowledge-based admissible models
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
Marek Grzes, Daniel Kudenko
AH
2008
Springer
14 years 3 months ago
A Validation Framework for Formal Models in Adaptive Work-Integrated Learning
The focus of my thesis is on the development of a multi-method framework for the validation of formal models (domain model, user model, and teaching model) for adaptive work-integr...
Barbara Kump
CIA
2006
Springer
14 years 13 days ago
Market-Inspired Approach to Collaborative Learning
The paper describes a decentralized peer-to-peer multi-agent learning method based on inductive logic programming and knowledge trading. The method uses first-order logic for model...
Jan Tozicka, Michal Jakob, Michal Pechoucek