Gita Sukthankar

The 2017 AAAI Spring Symposium Series Gita Sukthankar

The AAAI Spring Symposium Series is an annual set of meetings run in parallel at a common site. It is designed to bring colleagues together in an intimate forum while at the same time providing a significant gathering point for the AI community. The two and one half day format of the series allows participants to devote considerably more time to feedback and discussion than typical one- day workshops. It is an ideal venue for bringing together new communities in emerging fields.

The symposia are intended to encourage presentation of speculative work and work in progress, as well as completed work. Ample time is scheduled for discussion. Novel programming, including the use of target problems, open-format panels, working groups, or breakout sessions, is encour- aged. AAAI Technical Reports are prepared, and distributed to the participants. Most participants of the symposia were selected on the basis of statements of interest or abstracts submitted to the symposia chairs; some open registration is allowed. All symposia are limited in size, and partici- pants are expected to attend a single symposium.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, is pleased to present the 2017 Spring Symposium Series, held Monday through Wednesday, March 27-29, 2017 on the campus of Stanford University. The eight symposia are:

SS-17-01: Artificial Intelligence for the Social Good
SS-17-02: Computational Construction Grammar and Natural Language Understanding
SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed? SS-17-04: Designing the User Experience of Machine Learning Systems
SS-17-05: Interactive Multisensory Object Perception for Embodied Agents
SS-17-06: Learning from Observation of Humans
SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing