Acquisition, Learning & Demonstration: Automating Tasks for Users
Papers from the AAAI Spring Symposium
Automating tasks through interactions with users has always been recognized as an important area of research, one that will attract increasing attention in the next few years. Larger bodies of knowledge will need to be acquired and maintained as AI systems are scaled up and applied to real-world problems. The interactive nature of the growing Internet (where many services will be offered and diverse intelligent assistants created) will pose an increasing demand on tools that help users define tasks they want computers to accomplish for them.
Currently, researchers in three different communities are looking at different aspects of this problem. Machine learning researchers tend to look for ways to automate the acquisition process with algorithms that do explanation or induction based on a user's actions. Knowledge acquisition research, mainly motivated by the automation of knowledge-intensive tasks, concentrates on understanding how to structure the system's interaction with users based on the nature of the task to be automated. The area of programming by demonstration, which emerged from the user interface and human-computer interaction communities, offers more natural ways for nonprogrammers to automate tasks using systems that analyze the sequence of actions chosen by a user to perform a task. The primary purpose of this symposium is to bring together these communities in order to exchange ideas and approaches, and to gain a better understanding of the state of the art and the technological and research challenges that we need to address in getting computers to do intelligent tasks for users.