Multi-Agent Autonomy and Beyond: A Mathematician’s Life at GDMS

Ben Strasser (General Dynamics Mission Systems)

Multi-agent autonomy is a broad field touching a wide variety of topics, including control theory, hybrid system verification, game theory, reinforcement learning, information theory, and network optimization. Agents must carefully use limited computational resources to perform complex and collaborative tasks while contending with both in-team information imbalances and non-collaborating agents. This talk provides a high-level overview of the multi-agent autonomy problem space and identifies several practical and theoretical challenges we face. I discuss recent work in multi-agent autonomy and my experience as a mathematician at GDMS.  I recommend this talk for any mathematics students considering a career in industry, as well as all parties with interest in problems related to multi-agent autonomy.