David Bossens

• PI, Safety and desirability criteria for AI-controlled aerial drones on construction sites, UKRI TASHub

1. Bossens, D. M. & Bishop, N. Explicit Explore, Exploit, or Escape (E4): near-optimal safety-constrained reinforcement learning in polynomial time. Machine Learning, 112, 817–858. (2023)

2. Bossens, D. M., Ramchurn, S., & Tarapore, D. Resilient robot teams: a review integrating decentralised control, change-detection, and learning. Current Robotics Reports, 3, 85–95. (2022)

3. Bossens, D. M. & Tarapore, D. Quality-Diversity Meta-Evolution: customising behaviour spaces to a meta-objective. IEEE Transactions on Evolutionary Computation, 1171–1181. (2022)

4. Bossens, D.M. & Tarapore, D. On the use of feature-maps for improved quality-diversity meta-evolution. Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO 2021), 83–84. (2021)

5. Thomas, T., Bossens, D. M., & Tarapore, D. ASVLite: a high-performance simulator for autonomous surface vehicles. Proceedings of the International Conference on Robotics and Automation (ICRA 2021), 2249–2255. (2021)

6. Bossens, D. M., & Tarapore, D. Rapidly adapting robot swarms with Swarm Map-based Bayesian Optimisation. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2021). (2021)

7. Bossens, D. M. & Tarapore, D. QED: Using Quality-Environment-Diversity to Evolve Resilient Robot Swarms. IEEE Transactions on Evolutionary Computation, 25(2), 346–357. (2021)

8. Bossens, D. M., Mouret, J., & Tarapore, D. Learning behaviour-performance maps with meta-evolution. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2020), 49–57. (2020)

9. Bossens, D. M., Townsend, N. C., & Sobey, A. J. Learning to learn with active adaptive perception. Neural Networks, 115, 30–49. (2019)

• Reviewer at AAMAS, GECCO, ICRA, IROS, COLLAS conferences
• Co-organiser of Safe RL workshop at IJCAI 2022 and IJCAI 2023