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GECCO
2007
Springer
143views Optimization» more  GECCO 2007»
15 years 3 months ago
Learning and exploiting knowledge in multi-agent task allocation problems
Imagine a group of cooperating agents attempting to allocate tasks amongst themselves without knowledge of their own capabilities. Over time, they develop a belief of their own sk...
Adam Campbell, Annie S. Wu
IJCAI
2001
14 years 11 months ago
Exploiting Multiple Secondary Reinforcers in Policy Gradient Reinforcement Learning
Most formulations of Reinforcement Learning depend on a single reinforcement reward value to guide the search for the optimal policy solution. If observation of this reward is rar...
Gregory Z. Grudic, Lyle H. Ungar
ACL
2012
12 years 12 months ago
Exploiting Social Information in Grounded Language Learning via Grammatical Reduction
This paper uses an unsupervised model of grounded language acquisition to study the role that social cues play in language acquisition. The input to the model consists of (orthogr...
Mark Johnson, Katherine Demuth, Michael C. Frank
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
15 years 1 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
ICPR
2008
IEEE
15 years 10 months ago
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
Qiang Ji, Wenhui Liao