References of "Duflo, Gabriel 50031072"
     in
Bookmark and Share    
Full Text
Peer Reviewed
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)

Detailed reference viewed: 75 (2 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 77 (8 UL)
Full Text
Peer Reviewed
See detailLearning to Optimise a Swarm of UAVs
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

in Applied Sciences (2022), 12(19 9587),

The use of Unmanned Aerial Vehicles (UAVs) has shown a drastic increase in interest in the past few years. Current applications mainly depend on single UAV operations, which face critical limitations such ... [more ▼]

The use of Unmanned Aerial Vehicles (UAVs) has shown a drastic increase in interest in the past few years. Current applications mainly depend on single UAV operations, which face critical limitations such as mission range or resilience. Using several autonomous UAVs as a swarm is a promising approach to overcome these. However, designing an efficient swarm is a challenging task, since its global behaviour emerges solely from local decisions and interactions. These properties make classical multirobot design techniques not applicable, while evolutionary swarm robotics is typically limited to a single use case. This work, thus, proposes an automated swarming algorithm design approach, and more precisely, a generative hyper-heuristic relying on multi-objective reinforcement learning, that permits us to obtain not only efficient but also reusable swarming behaviours. Experimental results on a three-objective variant of the Coverage of a Connected UAV Swarm problem demonstrate that it not only permits one to generate swarming heuristics that outperform the state-of-the-art in terms of coverage by a swarm of UAVs but also provides high stability. Indeed, it is empirically demonstrated that the model trained on a certain class of instances generates heuristics and is capable of performing well on instances with a different size or swarm density. [less ▲]

Detailed reference viewed: 24 (1 UL)
Full Text
Peer Reviewed
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)

Detailed reference viewed: 50 (6 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 132 (36 UL)
Full Text
Peer Reviewed
See detailA Q-Learning Hyper-Heuristic for UAV Swarming
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

Scientific Conference (2020)

Detailed reference viewed: 121 (31 UL)
Full Text
Peer Reviewed
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)

Detailed reference viewed: 117 (20 UL)
Full Text
Peer Reviewed
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)

Detailed reference viewed: 319 (73 UL)
Full Text
Peer Reviewed
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: 281 (55 UL)