| Empirical evaluation methods for multiobjective reinforcement learning algorithms P Vamplew, R Dazeley, A Berry, R Issabekov, E Dekker Machine learning 84, 51-80, 2011 | 361 | 2011 |
| MORL-Glue: A benchmark suite for multi-objective reinforcement learning P Vamplew, D Webb, LM Zintgraf, DM Roijers, R Dazeley, R Issabekov, ... 29th Benelux Conference on Artificial Intelligence November 8–9, 2017 …, 2017 | 10 | 2017 |
| Attributes of expert anticipation should inform the design of virtual reality simulators to accelerate learning and transfer of skill S Müller, E Dekker, K Morris-Binelli, B Piggott, G Hoyne, W Christensen, ... Sports Medicine 53 (2), 301-309, 2023 | 9 | 2023 |
| A Study of Drug-Reaction Relationships in Australian Drug Safety Data MA Mamedov, GW Saunders, E Dekker Proceedings of the 2nd Australian Data Mining Workshop (ADM03). December …, 2003 | 4 | 2003 |
| An optimization approach to the study of drug-reaction relationships on the basis of adrac dataset: Neurological class of reactions M Mammadov, E Dekker, G Saunders Proc. of The Sixth International Conference on Optimization: Techniques and …, 2004 | 2 | 2004 |
| Correction to: Attributes of Expert Anticipation Should Inform the Design of Virtual Reality Simulators to Accelerate Learning and Transfer of Skill S Müller, E Dekker, K Morris-Binelli, B Piggott, G Hoyne, W Christensen, ... Sports Medicine (Auckland, NZ) 53 (2), 311, 2023 | 1 | 2023 |
| Adoption of immersive-virtual reality as an intrinsically motivating learning tool in parasitology E Dekker, D Whitburn, S Preston Virtual Reality 28 (3), 123, 2024 | | 2024 |
| Attributes of Expert Anticipation Should Inform the Design of Virtual Reality Simulators to Accelerate Learning and Transfer of Skill (Jul, 10.1007/s40279-022-01735-7, 2022) S Mueller, E Dekker, K Morris-Binelli, B Piggott, G Hoyne, W Christensen, ... SPORTS MEDICINE 53 (2), 311-311, 2023 | | 2023 |
Rustam IssabekovPhD Student, University of Ballarat在 students.ballarat.edu.au 的电子邮件经过验证
