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A sequential algorithm portfolio approach for black box optimization

Swarm and Evolutionary Computation, 2019
Abstract A large number of optimization algorithms have been proposed. However, the no free lunch (NFL) theorems inform us that no algorithm can solve all types of optimization problems. An approach, which can suggest the most suitable algorithm for different types of problems, is valuable.
Yaodong He   +3 more
openaire   +1 more source

Toward the optimization of a class of black box optimization algorithms

Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence, 2002
Many black box optimization algorithms have sufficient flexibility to allow them to adapt to the varying circumstances they encounter. These capabilities are of two primary sorts: user-determined choices among alternative parameters, operations, and logic structures; and the algorithm-determined alternative paths chosen during the process of seeking a ...
Gang Wang   +2 more
openaire   +1 more source

Policy Learning with an Efficient Black-Box Optimization Algorithm

International Journal of Humanoid Robotics, 2015
Robotic learning on real hardware requires an efficient algorithm which minimizes the number of trials needed to learn an optimal policy. Prolonged use of hardware causes wear and tear on the system and demands more attention from an operator. To this end, we present a novel black-box optimization algorithm, Reward Optimization with Compact Kernels ...
Jemin Hwangbo   +4 more
openaire   +2 more sources

Online Black-Box Algorithm Portfolios for Continuous Optimization

2014
In black-box function optimization, we can choose from a wide variety of heuristic algorithms that are suited to different functions and computation budgets. Given a particular function to be optimized, the problem we consider in this paper is how to select the appropriate algorithm.
Petr Baudis, Petr Posik
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The Algorithmic Black Box

Abstract Chapter 2 introduces basic concepts associated with AI, including machine learning and deep neural networks, and explains why AI tools are often considered “black boxes.” It considers why we are seeing a significant escalation in the use of these tools in national security settings, especially by the United States and China, and
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Optimization algorithms for black- box problems

Τα προβλήματα βελτιστοποίησης μαύρου κουτιού (BBO) είναι διαδεδομένα στη σύγχρονη επιστήμη και τη μηχανική, τα οποία προκύπτουν από υπολογιστικά δαπανηρές προσομοιώσεις ή φυσικά πειράματα όπου η αντικειμενική συνάρτηση και οι παράγωγοί της δεν είναι προσβάσιμες.
openaire   +1 more source

Opening the Black Box: In Search of Algorithmic Transparency

SSRN Electronic Journal, 2016
Given the importance of search engines for public access to knowledge and questions over their neutrality, there have been many theoretical debates about the regulation of the search market and the transparency of search algorithms. However, there is little research on how such debates have played out empirically in the policy sphere.
openaire   +1 more source

Parameter estimation of DC black-Box arc models using genetic algorithms

Electric Power Systems Research, 2021
Maria Cristina Tavares
exaly  

From black box to glass box: algorithmic explainability as a strategic decision

Information Economics and Policy, 2023
Xavier Lambin, Adrien Raizonville
openaire   +1 more source

A Reinforcement-Learning Style Algorithm for Black Box Automata

2022 20th ACM-IEEE International Conference on Formal Methods and Models for System Design (MEMOCODE), 2022
Itay Cohen 0001, Roi Fogler, Doron Peled
openaire   +1 more source

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