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ILP
2007
Springer
15 years 6 months ago
Building Relational World Models for Reinforcement Learning
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
ILP
2007
Springer
15 years 6 months ago
ILP : - Just Trie It
Abstract. Despite the considerable success of Inductive Logic Programming, deployed ILP systems still have efficiency problems when applied to complex problems. Several techniques ...
Rui Camacho, Nuno A. Fonseca, Ricardo Rocha, V&iac...
ILP
2007
Springer
15 years 6 months ago
Applying Inductive Logic Programming to Process Mining
The management of business processes has recently received a lot of attention. One of the most interesting problems is the description of a process model in a language that allows ...
Evelina Lamma, Paola Mello, Fabrizio Riguzzi, Serg...
ILP
2007
Springer
15 years 6 months ago
Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning
In reinforcement learning problems, an agent has the task of learning a good or optimal strategy from interaction with his environment. At the start of the learning task, the agent...
Tom Croonenborghs, Kurt Driessens, Maurice Bruynoo...
ILP
2007
Springer
15 years 6 months ago
Bias/Variance Analysis for Relational Domains
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
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