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» Problems of learning in multi-agent systems
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AAAI
2008
15 years 6 months ago
Clause Learning Can Effectively P-Simulate General Propositional Resolution
Currently, the most effective complete SAT solvers are based on the DPLL algorithm augmented by clause learning. These solvers can handle many real-world problems from application...
Philipp Hertel, Fahiem Bacchus, Toniann Pitassi, A...
SDM
2008
SIAM
140views Data Mining» more  SDM 2008»
15 years 5 months ago
Large-Scale Many-Class Learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Michael Connor
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
15 years 5 months ago
Multi-agent task allocation: learning when to say no
This paper presents a communication-less multi-agent task allocation procedure that allows agents to use past experience to make non-greedy decisions about task assignments. Exper...
Adam Campbell, Annie S. Wu, Randall Shumaker
118
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AOSE
2005
Springer
15 years 9 months ago
Aspects in Agent-Oriented Software Engineering: Lessons Learned
Several concerns in the development of multi-agent systems (MASs) cannot be represented in a modular fashion. In general, they inherently affect several system modules and cannot b...
Alessandro F. Garcia, Uirá Kulesza, Cl&aacu...
AICCSA
2006
IEEE
133views Hardware» more  AICCSA 2006»
15 years 10 months ago
Learning acyclic rules based on Chaining Genetic Programming
Multi-class problem is the class of problems having more than one classes in the data set. Bayesian Network (BN) is a well-known algorithm handling the multi-class problem and is ...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong