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JCP
2008
139views more  JCP 2008»
13 years 8 months ago
Agent Learning in Relational Domains based on Logical MDPs with Negation
In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
Song Zhiwei, Chen Xiaoping, Cong Shuang
JUCS
2008
186views more  JUCS 2008»
13 years 8 months ago
An Agent-Based Solution for Dynamic Supply Chain Management
: Supply chain management (SCM) deals with planning and coordinating activities such as material procurement, product assembly, and the distribution of manufactured products. This ...
Vedran Podobnik, Ana Petric, Gordan Jezic
JODS
2006
148views Data Mining» more  JODS 2006»
13 years 8 months ago
Discovering the Semantics of Relational Tables Through Mappings
Abstract. Many problems in Information and Data Management require a semantic account of a database schema. At its best, such an account consists of formulas expressing the relatio...
Yuan An, Alexander Borgida, John Mylopoulos
ML
2006
ACM
142views Machine Learning» more  ML 2006»
13 years 8 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
IJCSS
2007
97views more  IJCSS 2007»
13 years 8 months ago
Collaborative Multi-Agent-based e-Commerce Framework
Software agents offer a promise to change electronic commerce trading by helping traders to purchase products based on their interests and preferences. E-commerce systems are incr...
Tarek Helmy