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Antoine Ligot
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Automatic off-line design of robot swarms: a manifesto
M Birattari, A Ligot, D Bozhinoski, M Brambilla, G Francesca, L Garattoni, ...
Frontiers in Robotics and AI 6, 59, 2019
802019
Behavior trees as a control architecture in the automatic modular design of robot swarms
J Kuckling, A Ligot, D Bozhinoski, M Birattari
International conference on swarm intelligence, 30-43, 2018
562018
Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms
A Ligot, M Birattari
Swarm Intelligence 14 (1), 1-24, 2020
532020
Disentangling automatic and semi-automatic approaches to the optimization-based design of control software for robot swarms
M Birattari, A Ligot, K Hasselmann
Nature Machine Intelligence 2 (9), 494-499, 2020
432020
Empirical assessment and comparison of neuro-evolutionary methods for the automatic off-line design of robot swarms
K Hasselmann, A Ligot, J Ruddick, M Birattari
Nature communications 12 (1), 4345, 2021
412021
Reference models for AutoMoDe
K Hasselmann, A Ligot, G Francesca, M Birattari
IRIDIA, Université libre de Bruxelles, Brussels, Belgium, Tech. Rep. TR …, 2018
372018
AutoMoDe: a modular approach to the automatic off-line design and fine-tuning of control software for robot swarms
M Birattari, A Ligot, G Francesca
Automated design of machine learning and search algorithms, 73-90, 2021
272021
On mimicking the effects of the reality gap with simulation-only experiments
A Ligot, M Birattari
Swarm Intelligence: 11th International Conference, ANTS 2018, Rome, Italy …, 2018
242018
Concurrent design of control software and configuration of hardware for robot swarms under economic constraints
M Salman, A Ligot, M Birattari
PeerJ Computer Science 5, e221, 2019
202019
Automatic modular design of robot swarms using behavior trees as a control architecture
A Ligot, J Kuckling, D Bozhinoski, M Birattari
PeerJ Computer Science 6, e314, 2020
182020
AutoMoDe-arlequin: neural networks as behavioral modules for the automatic design of probabilistic finite-state machines
A Ligot, K Hasselmann, M Birattari
International Conference on Swarm Intelligence, 271-281, 2020
172020
Toward an empirical practice in offline fully automatic design of robot swarms
A Ligot, A Cotorruelo, E Garone, M Birattari
IEEE transactions on evolutionary computation 26 (6), 1236-1245, 2022
132022
Complexity measures: open questions and novel opportunities in the automatic design and analysis of robot swarms
A Roli, A Ligot, M Birattari
Frontiers in Robotics and AI 6, 130, 2019
102019
AutoMoDe, NEAT, and EvoStick: implementations for the e-puck robot in ARGoS3
A Ligot, K Hasselmann, B Delhaisse, L Garattoni, G Francesca, M Birattari
IRIDIA, Institut de Recherches Interdisciplinaires et de Développements en …, 2018
82018
On using simulation to predict the performance of robot swarms
A Ligot, M Birattari
Scientific Data 9 (1), 788, 2022
62022
Search space for AutoMoDe-Chocolate and AutoMoDe-Maple
J Kuckling, A Ligot, D Bozhinoski, M Birattari
Technical report TR/IRIDIA/2018-012, IRIDIA, Université Libre de Bruxelles …, 2018
62018
Automatic modular design of robot swarms based on repertoires of behaviors generated via novelty search
K Hasselmann, A Ligot, M Birattari
Swarm and Evolutionary Computation 83, 101395, 2023
42023
The automatic off-line design of robot swarms: recent advances and perspectives
DG Ramos, D Bozhinoski, G Francesca, L Garattoni, K Hasselmann, ...
R2T2: Robotics Research for Tomorrow’s Technology, 2021
42021
Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms. Swarm Intell. 14 (1), 1–24 (2019)
A Ligot, M Birattari
4
Assessing and forecasting the performance of optimization-based design methods for robot swarms: Experimental protocol and pseudo-reality predictors
A Ligot
Université libre de Bruxelles, 2023
32023
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