References of "Duflo, Gabriel 50031072"
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See detailA Framework of Hyper-Heuristics based on Q-Learning
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

in International Conference in Optimization and Learning (OLA2022) (2022)

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See detailA RNN-Based Hyper-Heuristic for Combinatorial Problems
Kieffer, Emmanuel UL; Duflo, Gabriel UL; Danoy, Grégoire UL et al

in A RNN-Based Hyper-Heuristic for Combinatorial Problems (2022)

Designing efficient heuristics is a laborious and tedious task that generally requires a full understanding and knowledge of a given optimization problem. Hyper-heuristics have been mainly introduced to ... [more ▼]

Designing efficient heuristics is a laborious and tedious task that generally requires a full understanding and knowledge of a given optimization problem. Hyper-heuristics have been mainly introduced to tackle this issue and are mostly relying on Genetic Programming and its variants. Many attempts in the literature have shown that an automatic training mechanism for heuristic learning is possible and can challenge human-based heuristics in terms of gap to optimality. In this work, we introduce a novel approach based on a recent work on Deep Symbolic Regression. We demonstrate that scoring functions can be trained using Recurrent Neural Networks to tackle a well-know combinatorial problem, i.e., the Multi-dimensional Knapsack. Experiments have been conducted on instances from the OR-Library and results show that the proposed modus operandi is an alternative and promising approach to human- based heuristics and classical heuristic generation approaches. [less ▲]

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See detailA Q-Learning Based Hyper-Heuristic for Generating Efficient UAV Swarming Behaviours
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

in Intelligent Information and Database Systems - 13th Asian Conference ACIIDS 2021, Phuket, Thailand, April 7-10, 2021, Proceedings (2021)

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See detailAutomating the Design of Efficient Distributed Behaviours for a Swarm of UAVs
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

in IEEE Symposium Series on Computational Intelligence, Canberra 1-4 December 2020 (2020, December)

The usage of Unmanned Aerial Vehicles (UAVs) is gradually gaining momentum for commercial applications. The vast majority considers a single UAV, which comes with several constraints such as its range of ... [more ▼]

The usage of Unmanned Aerial Vehicles (UAVs) is gradually gaining momentum for commercial applications. The vast majority considers a single UAV, which comes with several constraints such as its range of operations or the number of sensors it can carry. Using multiple autonomous UAVs simultaneously as a swarm makes it possible to overcome these limitations. However, manually designing complex emerging behaviours like swarming is a difficult and tedious task especially for such distributed systems which performance is hardly predictable. This article therefore proposes to automate the design of UAV swarming behaviours by defining a multi-objective optimisation problem, so called Coverage of a Connected-UAV Swarm (CCUS), and designing a Q-Learning based Hyper-Heuristic (QLHH) for generating distributed CCUS heuristics. Experimental results demonstrate the capacity of QLHH to generate efficient heuristics for any instance from a given class. [less ▲]

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See detailA Q-Learning Hyper-Heuristic for UAV Swarming
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

Scientific Conference (2020)

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See detailAutomated design of efficient swarming behaviours: a Q-learning hyper-heuristic approach
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

in GECCO '20: Genetic and Evolutionary Computation Conference, Companion Volume, Cancún, Mexico, July 8-12, 2020 (2020)

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See detailA GP Hyper-Heuristic Approach for Generating TSP Heuristics
Duflo, Gabriel UL; Kieffer, Emmanuel UL; Brust, Matthias R. UL et al

in 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS 2019) (2019, May 20)

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See detailGP hyper-heuristic for the travelling salesman problem
Duflo, Gabriel UL; Kieffer, Emmanuel UL; Danoy, Grégoire UL et al

Scientific Conference (2019, January 29)

Detailed reference viewed: 275 (55 UL)