We present the first temporal-difference learning algorithm for off-policy control with unrestricted linear function approximation whose per-time-step complexity is linear in the ...
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
This paper describes the use of a multi-objective evolution strategy in tuning a fuzzy controller which is used in sewage treatment plants. The controller adjusts the oxygenation ...
Patrick O. Stalph, Marc Ebner, Martin Michel, Bern...
We consider a multi-agent optimization problem where agents aim to cooperatively minimize a sum of local objective functions subject to a global inequality constraint and a global ...
We propose the use of a new algorithm to solve multiobjective optimization problems. Our proposal adapts the well-known scatter search template for single objective optimization to...
Antonio J. Nebro, Francisco Luna, Enrique Alba, Be...