With the ever increasing deployment and usage of gigabit networks, traditional network anomaly detection based Intrusion Detection Systems (IDS) have not scaled accordingly. Most,...
We present a new series of distributed constraint satisfaction algorithms, the distributed breakout algorithms, which is inspired by local search algorithms for solving the constr...
Combinatorial auctions, that is, auctions where bidders can bid on combinations of items, tend to lead to more efficient allocations than traditional auction mechanisms in multi-i...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Abstract-- We present a case study demonstrating that using the REVAC parameter tuning method we can greatly improve the `world champion' EA (the winner of the CEC2005 competi...