Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
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...
Component-based models represent a dominant trend in the construction of wide-area network applications, making possible the integration of diverse functionality contained in modu...
We model budget-constrained keyword bidding in sponsored search auctions as a stochastic multiple-choice knapsack problem (S-MCKP) and design an algorithm to solve S-MCKP and the ...
This work proposes a parallel memetic algorithm applied to the total tardiness single machine scheduling problem. Classical models of parallel evolutionary algorithms and the gene...