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GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 8 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
TNN
1998
146views more  TNN 1998»
15 years 4 months ago
Fuzzy lattice neural network (FLNN): a hybrid model for learning
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
Vassilios Petridis, Vassilis G. Kaburlasos
APSCC
2008
IEEE
15 years 11 months ago
Adaptive Learning Sequencing for Course Customization: A Web Service Approach
— We discuss a learning model that enables the creation of optimal learning strategies that suit learners’ needs. A customized learning content is delivered to learners as mana...
Ivan Madjarov, Abdelkader Bétari
AAAI
2007
15 years 6 months ago
Mapping and Revising Markov Logic Networks for Transfer Learning
Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...
Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Moon...
EUSFLAT
2003
122views Fuzzy Logic» more  EUSFLAT 2003»
15 years 5 months ago
Structure recognition on sequences with a neuro-fuzzy-system
We present a formal description of a neurofuzzy system capable of aligning two sequences recognizing their internal structure. The alignment is done on two levels: grouping of the...
Klaus Dalinghaus, Tillman Weyde