Leveraging Human Feedback to Evolve and Discover Novel Emergent Behaviors in Robot Swarms. - Connor Mattson; Daniel S. Brown (GECCO, 2023)

Exploring Behavior Discovery Methods for Heterogeneous Swarms of Limited-Capability Robots. - Connor Mattson; Jeremy C. Clark; Daniel S. Brown (MRS, 2023)

Swarm Mechanics and Swarm Chemistry: A Transdisciplinary Approach for Robot Swarms. - Ricardo Vega; Kevin Zhu; Connor Mattson; Daniel S. Brown; Cameron Nowzari (CoRR, 2023)

Spiking Neural Networks as a Controller for Emergent Swarm Agents. - Kevin Zhu; Connor Mattson; Shay Snyder; Ricardo Vega; Daniel S. Brown; Maryam Parsa; Cameron Nowzari (ICONS, 2024)

Representation Alignment from Human Feedback for Cross-Embodiment Reward Learning from Mixed-Quality Demonstrations. - Connor Mattson; Anurag Aribandi; Daniel S. Brown (RLJ, 2024)

Agent-Based Emulation for Deploying Robot Swarm Behaviors. - Ricardo Vega; Kevin Zhu; Connor Mattson; Daniel S. Brown; Cameron Nowzari (CoRR, 2024)

Toward Zero-Shot User Intent Recognition in Shared Autonomy. - Atharv Belsare; Zohre Karimi; Connor Mattson; Daniel S. Brown (HRI, 2025)

Discovery and Deployment of Emergent Robot Swarm Behaviors via Representation Learning and Real2Sim2Real Transfer. - Connor Mattson; Varun Raveendra; Ricardo Vega; Cameron Nowzari; Daniel S. Drew; Daniel S. Brown (AAMAS, 2025)