| Prosthetic rehabilitation training in virtual reality D Dhawan, M Barlow, E Lakshika 2019 IEEE 7th international conference on serious games and applications for …, 2019 | 30 | 2019 |
| A data driven review of board game design and interactions of their mechanics D Samarasinghe, M Barlow, E Lakshika, T Lynar, N Moustafa, ... IEEE access 9, 114051-114069, 2021 | 29 | 2021 |
| Wearable sensors for recognizing individuals undertaking daily activities SA Elkader, M Barlow, E Lakshika Proceedings of the 2018 ACM international symposium on wearable computers, 64-67, 2018 | 26 | 2018 |
| Analysis and prediction of player population changes in digital games during the COVID-19 pandemic D Wannigamage, M Barlow, E Lakshika, K Kasmarik Australasian Joint Conference on Artificial Intelligence, 458-469, 2020 | 15 | 2020 |
| Automatic synthesis of swarm behavioural rules from their atomic components D Samarasinghe, E Lakshika, M Barlow, K Kasmarik Proceedings of the Genetic and Evolutionary Computation Conference, 133-140, 2018 | 15 | 2018 |
| Understanding the interplay of model complexity and fidelity in multiagent systems via an evolutionary framework E Lakshika, M Barlow, A Easton IEEE Transactions on Computational Intelligence and AI in Games 9 (3), 277-289, 2016 | 15 | 2016 |
| Co-evolving semi-competitive interactions of sheepdog herding behaviors utilizing a simple rule-based multi agent framework E Lakshika, M Barlow, A Easton 2013 IEEE Symposium on Artificial Life (ALIFE), 82-89, 2013 | 14 | 2013 |
| Mental workload classification using short duration EEG data: an ensemble approach based on individual channels N Salimi, M Barlow, E Lakshika 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 393-398, 2019 | 11 | 2019 |
| Heart rate and breathing variability for virtual reality game play T Charoensook, M Barlow, E Lakshika 2019 IEEE 7th international conference on serious games and applications for …, 2019 | 11 | 2019 |
| Weekly seasonal player population patterns in online games: A time series clustering approach D Vihanga, M Barlow, E Lakshika, K Kasmarik 2019 IEEE Conference on Games (CoG), 1-8, 2019 | 9 | 2019 |
| Machine education-the way forward for achieving trust-enabled machine agents G Leu, E Lakshika, J Tang, K Merrick, M Barlow NIPS’17 Workshop: Teaching Machines, Robots, and Humans, 2017 | 9 | 2017 |
| Fidelity and complexity of standing group conversation simulations: A framework for the evolution of multi agent systems through bootstrapping human aesthetic judgments E Lakshika, M Barlow, A Easton 2012 IEEE Congress on Evolutionary Computation, 1-8, 2012 | 9 | 2012 |
| Exploiting abstractions for grammar‐based learning of complex multi‐agent behaviours D Samarasinghe, M Barlow, E Lakshika, K Kasmarik International Journal of Intelligent Systems 36 (11), 6273-6311, 2021 | 7 | 2021 |
| Flow-based reinforcement learning D Samarasinghe, M Barlow, E Lakshika IEEE Access 10, 102247-102265, 2022 | 6 | 2022 |
| Grammar-based cooperative learning for evolving collective behaviours in multi-agent systems D Samarasinghe, M Barlow, E Lakshika, K Kasmarik Swarm and Evolutionary Computation 69, 101017, 2022 | 6 | 2022 |
| Reinforcement Learning Agents Playing Ticket to Ride–A Complex Imperfect Information Board Game With Delayed Rewards S Yang, M Barlow, T Townsend, X Liu, D Samarasinghe, E Lakshika, ... IEEE Access 11, 60737-60757, 2023 | 5 | 2023 |
| Activity-independent person identification based on daily activities using wearable sensors S Hussein, M Barlow, E Lakshika AI 2020: Advances in Artificial Intelligence: 33rd Australasian Joint …, 2020 | 5 | 2020 |
| Towards Potential of N-back Task as Protocol and EEGNet for the EEG-based Biometric N Salimi, M Barlow, E Lakshika 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1718-1724, 2020 | 4 | 2020 |
| What cost teamwork: quantifying situational awareness and computational requirements in a proto-team via multi-objective evolution M Barlow, E Lakshika 2016 IEEE Congress on Evolutionary Computation (CEC), 3525-3532, 2016 | 4 | 2016 |
| Evolving lane merge traffic behaviour simulations via a macroscopic objective function and a machine learning system trained through bootstrapped human judgement E Lakshika, M Barlow, A Easton Applied Intelligence 44 (4), 862-877, 2016 | 4 | 2016 |
