David M. Bossens

Orcid: 0000-0003-1924-5756

According to our database1, David M. Bossens authored at least 17 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Lifetime policy reuse and the importance of task capacity.
AI Commun., 2024

2023
Explicit Explore, Exploit, or Escape (E<sup>4</sup>): near-optimal safety-constrained reinforcement learning in polynomial time.
Mach. Learn., March, 2023

Robust Lagrangian and Adversarial Policy Gradient for Robust Constrained Markov Decision Processes.
CoRR, 2023

2022
Quality-Diversity Meta-Evolution: Customizing Behavior Spaces to a Meta-Objective.
IEEE Trans. Evol. Comput., 2022

Low Variance Off-policy Evaluation with State-based Importance Sampling.
CoRR, 2022

Trust in Language Grounding: a new AI challenge for human-robot teams.
CoRR, 2022

Resilient robot teams: a review integrating decentralised control, change-detection, and learning.
CoRR, 2022

2021
QED: Using Quality-Environment-Diversity to Evolve Resilient Robot Swarms.
IEEE Trans. Evol. Comput., 2021

Quality-Diversity Meta-Evolution: customising behaviour spaces to a meta-objective.
CoRR, 2021

On the use of feature-maps and parameter control for improved quality-diversity meta-evolution.
CoRR, 2021

ASVLite: a high-performance simulator for autonomous surface vehicles.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Rapidly adapting robot swarms with Swarm Map-based Bayesian Optimisation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

On the use of feature-maps for improved quality-diversity meta-evolution.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020
Reinforcement learning with limited prior knowledge in long-term environments.
PhD thesis, 2020

ASV-Swarm: a high-performance simulator for the dynamics of a swarm of autonomous marine vehicles in waves.
CoRR, 2020

Learning behaviour-performance maps with meta-evolution.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019
Learning to learn with active adaptive perception.
Neural Networks, 2019


  Loading...