Biography
Understanding the interactions between agents is important to understanding multi-agent systems. Jennifer's work focuses on communication networks in deep reinforcement learning systems (using distributed reinforcement learning or multi-agent reinforcement learning algorithms). Her primary research outputs are novel algorithms that leverage communication networks to outperform previous state-of-the-art work. She also uses tools from network analysis and graph theory to gain insights into the behaviour of these algorithms and systems.