David M. Bossens

According to our database, David M. Bossens authored at least 19 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

The Digital Ecosystem of Beliefs: does evolution favour AI over humans?

David M. Bossens, Shanshan Feng, Yew-Soon Ong

CoRR, 2024

Quantum Policy Gradient in Reproducing Kernel Hilbert Space.

David M. Bossens, Kishor Bharti, Jayne Thompson

CoRR, 2024

Lifetime policy reuse and the importance of task capacity.

David M. Bossens, Adam J. Sobey

AI Commun., 2024

2023

Explicit Explore, Exploit, or Escape (E⁴): near-optimal safety-constrained reinforcement learning in polynomial time.

David M. Bossens, Nicholas Bishop

Mach. Learn., March, 2023

Robust Lagrangian and Adversarial Policy Gradient for Robust Constrained Markov Decision Processes.

David M. Bossens

CoRR, 2023

2022

Quality-Diversity Meta-Evolution: Customizing Behavior Spaces to a Meta-Objective.

David M. Bossens, Danesh Tarapore

IEEE Trans. Evol. Comput., 2022

Low Variance Off-policy Evaluation with State-based Importance Sampling.

David M. Bossens, Philip Thomas

CoRR, 2022

Trust in Language Grounding: a new AI challenge for human-robot teams.

David M. Bossens, Christine Evers

CoRR, 2022

Resilient robot teams: a review integrating decentralised control, change-detection, and learning.

David M. Bossens, Sarvapali D. Ramchurn, Danesh Tarapore

CoRR, 2022

2021

QED: Using Quality-Environment-Diversity to Evolve Resilient Robot Swarms.

David M. Bossens, Danesh Tarapore

IEEE Trans. Evol. Comput., 2021

Quality-Diversity Meta-Evolution: customising behaviour spaces to a meta-objective.

David M. Bossens, Danesh Tarapore

CoRR, 2021

On the use of feature-maps and parameter control for improved quality-diversity meta-evolution.

David M. Bossens, Danesh Tarapore

CoRR, 2021

ASVLite: a high-performance simulator for autonomous surface vehicles.

Toby Thomas, David M. Bossens, Danesh Tarapore

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Rapidly adapting robot swarms with Swarm Map-based Bayesian Optimisation.

David M. Bossens, Danesh Tarapore

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

On the use of feature-maps for improved quality-diversity meta-evolution.

David M. Bossens, Danesh Tarapore

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020

Reinforcement learning with limited prior knowledge in long-term environments.

David M. Bossens

PhD thesis, 2020

ASV-Swarm: a high-performance simulator for the dynamics of a swarm of autonomous marine vehicles in waves.

Toby Thomas, David M. Bossens, Danesh Tarapore

CoRR, 2020

Learning behaviour-performance maps with meta-evolution.

David M. Bossens, Jean-Baptiste Mouret, Danesh Tarapore

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019

Learning to learn with active adaptive perception.

David M. Bossens, Nicholas C. Townsend, Adam J. Sobey

Neural Networks, 2019