AGI17UUW: AGI-17 Understand Understanding Workshop AGI-17 Melbourne, Australia, August 18, 2017 |
Conference website | http://www.agi-conf.org/2017/workshops/ |
Abstract registration deadline | July 10, 2017 |
Submission deadline | July 10, 2017 |
Understanding Understanding will be a one-day workshop addressing recent work relevant to the question of machine understanding, aiming for a wide range of topics and methods to be presented and discussed. To explore the natural questions inherent within this concept the workshop aims to draw on the fields of AI, AGI, philosophy, cognitive science and psychology to cover a diverse set of methods, assumptions, approaches, and systems design and thinking in the field of AI and AGI.
Understanding seems central to the human ability to assess our own capacity for affecting change in particular contexts on particular tasks. Most humans not trained in mountain climbing will turn down an offer to climb Mount Everest. They also have an easy time explaining why they turn it down, and can probably cook up a rough outline for the kind of training that might make them change their mind. We call it a lack of understanding when issues central to a topic or problem are blissfully ignored by someone trying to solve it, and consider it a hopeless case when repeated attempts at explaining to them that they don't have sufficient understanding of the subject to make any important decisions about it are ignored.
Historically, the use of the term understanding in AI has mostly focused on natural language, which relates to the parsing and manipulation of linguistic tokens, and scene or image understanding, which again relates to parsing or largely semantics-free processing, with any discussion of understanding proper a rare occurrence. To the field of AGI, for which the topic of generality is central, this state of affairs would seem far from ideal. To investigate the phenomenon of understanding, compare systems with respect to their potential for understanding, and get to the crux of what understanding really is, seems important enough to give it more scrutiny.
We are interested in submissions from the fields on AGI, AI, psychology, and philosophy, which focus upon the concept of understanding, especially in relation to the goal of building machines that have the capacity to understand.
Among the questions and topics the workshop will address (but is not limited to) are the following:
- How should we define understanding?
- How can we test for understanding?
- Is understanding an emergent property of intelligent systems?
- Is understanding a central property of intelligent systems?
- What are the typologies or gradations of understanding?
- How can we create systems that exhibit understanding?
- What is required in order to achieve understanding in machines?
- Can understanding be achieved through hand-crafted architectures or must it emerge through self-organizing (constructivist) principles?
- How can mainstream techniques be used towards the development of machines which exhibit understanding?
- Do we need radically different approaches than those in use today to build systems with understanding?
- Does building artificially intelligent machines with versus without understanding depend on the same underlying principles, or are these orthogonal approaches?
- Do we need special programming languages to implement understanding in intelligent systems?
- Is general intelligence necessary and/or sufficient to achieve understanding in an artificial system?
- What differentiates systems that do and do not have understanding?
- How can current state of the art methods in AGI address the need for understanding in machines?
Submission Guidelines
Papers should be between 2 and 12 pages (excluding references) and describe the authors' original work in full (no extended abstracts). Formatting can follow either the AGI-17 format or the IJCAI-17 format. Papers should include a running head specifying which of the two formats was used. Papers will be subjected to peer-review and can be accepted for oral presentation or poster presentation.
Proposals for Demonstrations should be accompanied with a 2-page extended abstract for inclusion in the workshop's proceedings. Examples include, but are not limited to: (interactively) demonstrating the performance of a system, (cognitive) architecture, or design methodology.
Oral presentations should be given by one of the authors during one of the Contributed Talks Sessions. Posters and demonstrations will be presented during the Poster & Demo Session at the end of the day, and authors will be given a few minutes to promote their work during the Poster & Demo Session. Accepted papers will be gathered into a volume of proceedings and published online.
Contributions should be submitted through EasyChair by the deadline on June 20th (23:59 Eastern time). Authors will be notified on June 30th of the acceptance or rejection of their submission, and are requested to submit a revised camera-ready version based on reviewers' comments by August 5th.
List of Topics
- Design proposals for cognitive architectures targeting understanding
- New programming languages relevant to understanding
- New methods relevant to understanding
- New architectural principles relevant to understanding
- New theoretical insights relevant to understanding
- Synergies between various approaches to understanding (theoretically, within AGI, etc.)
- Machine education/learning needed to achieve understanding
- Analysis of the potential and limitations of existing approaches
Committees
Program Committee
- Joscha Bach
- Tarek Richard Besold
- Jordi Bieger
- Antonio Chella
- Haris Dindo
- Helgi P. Helgason
- David Kremelberg
- Xiang Li
- Tony Lofthouse
- Laurent Orseau
- Javier Snaider
- Bas Steunebrink
- Claes Strannegård
- Kristinn R. Thórisson
- Pei Wang
Organizing committee
- David Kremelberg
- Kristinn R. Thórisson
- Pei Wang
- Bas Steunebrink
Venue
The conference will be held in Melbourne, Australia on August 18th, 2017.
Contact
All questions about submissions should be emailed to the organizing committee chair at david.kremelberg@gmail.com