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» Building Relational World Models for Reinforcement Learning
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IJCAI
2003
13 years 7 months ago
Bayesian Information Extraction Network
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Leonid Peshkin, Avi Pfeffer
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
14 years 6 months ago
A multi-relational approach to spatial classification
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
Richard Frank, Martin Ester, Arno Knobbe
ECAI
2006
Springer
13 years 9 months ago
Agents with Anticipatory Behaviors: To Be Cautious in a Risky Environment
This work presents some anticipatory mechanisms in an agent architecture, modeling affective behaviours as effects of surprise. Through experiment discussion, the advantages of bec...
Cristiano Castelfranchi, Rino Falcone, Michele Piu...
CIKM
2009
Springer
13 years 10 months ago
Heterogeneous cross domain ranking in latent space
Traditional ranking mainly focuses on one type of data source, and effective modeling still relies on a sufficiently large number of labeled or supervised examples. However, in m...
Bo Wang, Jie Tang, Wei Fan, Songcan Chen, Zi Yang,...
SEMWEB
2007
Springer
13 years 12 months ago
Cultural Adaptivity for the Semantic Web
Our research explores the possibilities for factoring culture into user models, working towards cultural adaptivity in the semantic web. The aim is to represent the user’s positi...
Katharina Reinecke