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Luke Marsh
Luke Marsh
Defence Science and Technology Group
Verified email at dst.defence.gov.au
Title
Cited by
Cited by
Year
Multi-agent UAV path planning
L Marsh, G Calbert, J Tu, D Gossink, H Kwok
Proc Modelling and Simulation Society of Australia & New Zealand, Melbourne, 2005
232005
UAV team formation for emitter geolocation
L Marsh, D Gossink, SP Drake, G Calbert
2007 Information, Decision and Control, 176-181, 2007
192007
Multi-agent coordination and optimisation in the RoboCup Rescue project
WYJ Chou, L Marsh, D Gossink
18th World IMACS/MODSIM Congress. Cairns, Australia (July), 2009
82009
A systematic review of coevolution in real-time strategy games
EZ Elfeky, S Elsayed, L Marsh, D Essam, M Cochrane, B Sims, R Sarker
IEEE Access 9, 136647-136665, 2021
72021
Machine learning for adversarial agent microworlds
J Scholz, B Hengst, G Calbert, A Antoniades, P Smet, L Marsh, HW Kwok, ...
MODSIM 2005 International Congress on Modelling and Simulation, Modelling …, 2005
62005
Autonomous target allocation recommendations
L Marsh, M Cochrane, R Lodge, B Sims, J Traish, R Xu
2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1403-1410, 2020
32020
Reinforcement learning with model predictive control-recent development
T Tran, L Marsh, R Hunjet
Conference paper, ICOCTA, Sidney, 2019
22019
Machine learning approach for task generation in uncertain environments
L Marsh, I Dzieciuch, D Lange
2017 AAAI Spring Symposium Series, 2017
22017
Coevolutionary algorithm for evolving competitive strategies in the weapon target assignment problem
E Elfeky, M Cochrane, L Marsh, S Elsayed, B Sims, S Crase, D Essam, ...
Proceedings of the 2022 6th International Conference on Intelligent Systems …, 2022
12022
Negotiation Protocol Comparison for Task Allocation in Highly Dynamic Environments
K Noack, L Marsh, S Shekh
MOD-SIM2015, 21st International Congress on Modelling and Simulation …, 2015
12015
Exploiting Symmetries in Logistics Distribution Planning
L Marsh, D Gossink
19th International Congress on Modelling and Simulation, 482-488, 2011
12011
A Hybrid Multi-Modal Approach For Flocking
R Lodge, M Zamani, L Marsh, B Sims, R Hunjet
2019 12th Asian Control Conference (ASCC), 126-131, 2019
2019
Machine Learning Approach for Task Generation in Uncertain Contexts
L Marsh, I Dzieciuch, DS Lange
Computational Context, 97-106, 2018
2018
Assessing Supply Chain Robustness Through Stress Testing
S Shekh, L Marsh
The Twenty-Ninth International Flairs Conference, 2016
2016
Multi-Agent Distribution Planning
L Marsh, S Shekh, T Allard, HW Kwok, D Gossink
A Heuristic Planning Algorithm For Highly Constrained Maximum on Ground Problems
S Shekh, L Marsh
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Articles 1–16