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EMO
2009
Springer
190views Optimization» more  EMO 2009»
14 years 2 months ago
Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms
Abstract. Bilevel optimization problems require every feasible upperlevel solution to satisfy optimality of a lower-level optimization problem. These problems commonly appear in ma...
Kalyanmoy Deb, Ankur Sinha
BMCBI
2007
146views more  BMCBI 2007»
13 years 7 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
SAB
2010
Springer
189views Optimization» more  SAB 2010»
13 years 5 months ago
TeXDYNA: Hierarchical Reinforcement Learning in Factored MDPs
Reinforcement learning is one of the main adaptive mechanisms that is both well documented in animal behaviour and giving rise to computational studies in animats and robots. In th...
Olga Kozlova, Olivier Sigaud, Christophe Meyer
ATAL
2011
Springer
12 years 7 months ago
Quality-bounded solutions for finite Bayesian Stackelberg games: scaling up
The fastest known algorithm for solving General Bayesian Stackelberg games with a finite set of follower (adversary) types have seen direct practical use at the LAX airport for o...
Manish Jain, Christopher Kiekintveld, Milind Tambe
AAAI
2008
13 years 10 months ago
Efficient Algorithms to Solve Bayesian Stackelberg Games for Security Applications
In a class of games known as Stackelberg games, one agent (the leader) must commit to a strategy that can be observed by the other agent (the adversary/follower) before the advers...
Praveen Paruchuri, Jonathan P. Pearce, Janusz Mare...