This project uses the realm of believable improvisational performance agents to investigate the larger issues of scalability and robustness, which have long been problematic in AI systems. In general, AI systems have either been prone to a brittleness that results in a dramatic drop off in competence at the edges of their knowledge bases or a hyper explosion of inference in those cases where the knowledge bases are massive. These phenomena reflect a tension between the breadth of knowledge needed by a system to cover more than a single domain and the control needed to ensure that the resulting knowledge base can be used efficiently and effectively. In this project, issues of control and breadth are decoupled and handled by two very different sorts of systems. Control is handled by a variant of case-based (or example-based) planning, which will provide task-level guidance to information acquisition, evaluation, and application. Breadth is provided by the use of lexical technologies from the information retrieval community, which will be used to mine online resources. The case-based planning component will be used to create the queries and requirements that will then be used to control the information access performed by the retrieval mechanisms. The goal is to build a robust and scalable system that is able to provide breadth of coverage without sacrificing the power of control provided by the reasoning system. The choice of believable performance agents as an application domain provides highly visible constraints and evaluation metrics. On one hand, the agents must make use of the control of AI in order to produce the appropriate experience while, on the other, also be on point with regard to issues of information relevance, topicality, and point of view. This work is, in part, aimed at a new role for the machine in the world: a role in which the machine is used to expose the world of communication and cultural connections that are linked together by and within the grasp of online systems. The broader impacts of this work would range from creation of particular performance agents to more robust and scalable visions for AI. The project seeks to attract a wider set of students (including the underrepresented group of women in engineering) from communications studies and theater, who want to do work on the machine as a device for communication, communication made possible and supported by the mediation of intelligent systems.
