Results 21 to 30 of about 65,077 (195)
Efficient Elitist Cooperative Evolutionary Algorithm for Multi-Objective Reinforcement Learning
IEEE Access, 2023 Sequential decision-making problems with multiple objectives are known as multi-objective reinforcement learning. In these scenarios, decision-makers require a complete Pareto front that consists of Pareto optimal solutions. Such a front enables decision-
Dan Zhou, Jiqing Du, Sachiyo Arai
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Deep Q-Managed: a new framework for multi-objective deep reinforcement learning. [PDF]
Front Artif IntellThis paper introduces Deep Q-Managed, a novel multi-objective reinforcement leaning (MORL) algorithm designed to discover all policies within the Pareto Front.
Menezes R +3 more
europepmc +2 more sources
Automatic Discovery of Privacy–Utility Pareto Fronts [PDF]
Proceedings on Privacy Enhancing Technologies, 2020 Abstract Differential privacy is a mathematical framework for privacy-preserving data analysis. Changing the hyperparameters of a differentially private algorithm allows one to trade off privacy and utility in a principled way. Quantifying this trade-off in advance is essential to decision-makers tasked with deciding how much privacy can
Avent, Brendan +4 more
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Improved sampling of the pareto-front in multiobjective genetic optimizations by steady-state evolution: a Pareto converging genetic algorithm [PDF]
, 2002 Previous work on multiobjective genetic algorithms has been focused on preventing genetic drift and the issue of convergence has been given little attention.
Goldberg D. E. +4 more
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Two Objective Public Service System Design Problem
Communications, 2021 The public service system serves population spread over a geographical area from a given number of service centers. One of the possible approaches to the problem with two or more simultaneously applied contradicting objectives is ...
Jaroslav Janáček +3 more
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Multiplicative Approximations, Optimal Hypervolume Distributions, and the Choice of the Reference Point [PDF]
, 2013 Many optimization problems arising in applications have to consider several objective functions at the same time. Evolutionary algorithms seem to be a very natural choice for dealing with multi-objective problems as the population of such an algorithm ...
Friedrich, Tobias +2 more
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Pareto Joint Inversion of 2D magnetometric and gravity data- synthetic study [PDF]
E3S Web of Conferences, 2019 Pareto joint inversion for two or more data sets is an attractive and promising tool which eliminates target functions weighing and scaling, providing a set of acceptable solutions composing a Pareto front.
Danek Tomasz +3 more
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Physics and Imaging in Radiation Oncology, 2020 Introduction: Radiotherapy treatment planning is a multi-criteria problem. Any optimization of the process produces a set of mathematically optimal solutions.
A. Kyroudi +5 more
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Shanghai Jiaotong Daxue xuebao, 2021 In this paper, an optimal sizing and placement model for distributed generation (DG) is established, which includes active power losses, voltage profile, pollution emission, DG costs, and meteorological conditions.
YANG Bo, YU Lei, WANG Junting, SHU Hongchun, CAO Pulin, YU Tao
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Dynamic selection of a video content adaptation strategy from a Pareto front [PDF]
, 2008 This article is available open access through the publisher’s website through the link below. Copyright @ 2008 The Authors.Genetic Algorithms may be used together with Pareto Optimality in the process of selection of a suitable video content adaptation ...
Angelides, MC, Sofokleous, AA
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