The overall objective of my research is to develop methods for principled design that promotes effective multi-agent collaboration and enhances the way autonomous
virtual agents and robots interact with each other and with humans. To accomplish this objective, the focus of my work in the area of artificial intelligence (AI) is on multi-agent environment design which involves taking into account the constraints, limitations, and capabilities of the different agents in an AI system, and finding the best way to design their environment so that it complements the agents’ capabilities and compensates for their limitations.
My focus at CRCS is on environments with multiple self-interested agents that share a set of limited resources. The objective is to use different AI tools, such as automated planning, reinforcement learning, and game theory, to understand why specific behaviors emerge in such settings and to find the best way to change the environment in order to promote an effective collaboration between the agents. To evaluate our approach we are using multi-robot domains and sequential social dilemma settings, where we are using automated design to promote sustainable and socially aware behaviors of the agents in the system.