When autonomous agents model other agents: An appeal for altered judgment coupled with mouths, ears, and a little more tape

摘要

Agent modeling has rightfully garnered much attention in the design and study of autonomous agents that interact with other agents. However, despite substantial progress to date, existing agent-modeling methods too often (a) have unrealistic computational requirements and data needs; (b) fail to properly generalize across environments, tasks, and associates; and (c) guide behavior toward inefficient (myopic) solutions. Can these challenges be overcome? Or are they just inherent to a very complex problem? In this reflection, I argue that some of these challenges may be reduced by, first, modeling alternative processes than what is often modeled by existing algorithms and, second, considering more deeply the role of non-binding communication signals. Additionally, I believe that progress in developing autonomous agents that effectively interact with other agents will be enhanced as we develop and utilize a more comprehensive set of measurement tools and benchmarks. I believe that further development of these areas is critical to creating autonomous agents that effectively model and interact with other agents.