[DL] CFP: AAAI 2025 Workshop on Knowledge Axiomatization

[Vinay K Chaudhri]

  Call for Papers


  AAAI 2025 Workshop on


  Translational Institute for Knowledge Axiomatization (TIKA)

Workshop Website: https://sites.google.com/view/tika-2025/

Three critical revolutions 
<https://www.youtube.com/live/LqwL3CFVG8I?t=3614s> are shaping the 
landscape of AI: deep learning, knowledge graphs and automated 
reasoning. While deep learning has unleashed powerful tools such as 
ChatGPT, knowledge graphs and automated reasoning are providing 
essential backbone services for major corporations through applications 
such as business intelligence and automated verification.The National AI 
Research Resource (NAIRR 
<https://new.nsf.gov/focus-areas/artificial-intelligence/nairr>) is 
addressing all aspects of deep learning.There is, however, no similar 
resource pooling for knowledge graphs and automated reasoning. The goal 
of this workshop is to catalyze a global effort to fill this gap by 
creating a Translational Institute for Knowledge Axiomatization (TIKA). 
TIKA is envisioned to serve as a hub for research, education, training, 
and hosting of repositories of open-source knowledge based on open data 
sources. The institute would focus on "use-inspired" research, 
addressing pragmatic issues in translating advances in knowledge graphs 
and reasoning to practice.


  Topics of Interest

TIKA is envisioned to consider explicit knowledge in all forms including 
structured data, rules, controlled languages, mathematical formulas, 
etc. While AI for science must incorporate domain intelligence, it 
should also include knowledge to enable common sense reasoning and deep 
inferential reasoning that commercial knowledge graphs do not do today. 
The objectives of TIKA would be to pursue more human like learning that 
would be much more efficient and would not require as much training data 
and effort as the current generation of deep learning. This form of 
learning has also been referred to as "learning by being told" in the 
sense of McCarthy's advice taker 
<http://jmc.stanford.edu/artificial-intelligence/slides/advice03-sli.pdf>. 
TIKA is to advance the state-of-the-art in knowledge axiomatization by 
taking into account experience  from prior efforts such as Cyc 
<https://dl.acm.org/doi/abs/10.1145/219717.219745>, Project Halo 
<https://ojs.aaai.org/aimagazine/index.php/aimagazine/article/view/1783>, 
Wolfram Alpha <https://www.wolframalpha.com/>, ProtoOKN 
<https://www.proto-okn.net/> and the Linguistic Data Consortium 
<https://www.ldc.upenn.edu/>. As the goal of the workshop is to serve as 
a launchpad for TIKA with input from the broader AI community, we 
welcome submissions on topics that will constructively advance this 
mission. Some (but not all) of the topics include:

·Use Cases for Knowledge Axiomatization

·Educational Resources for TIKA

·Technical Resources for TIKA (e.g., computational representations, 
ontologies, domain models, reasoners, etc.)

·Approaches to transition from domain-specific (little semantics) to 
broader, more generalized systems (big semantics)

·Semantic Challenges in Enterprise Data Architectures

·Impact of Cyc and related efforts including lessons for TIKA

·Technical Roadmaps for TIKA including research challenges

·Turing Tests for Knowledge Axiomatization


  Workshop Format

The workshop will take place over two days, featuring a mixture of 
invited talks, panel discussions, and contributed presentations.

Attendance

Attendance is based on invitation.


  Submission Guidelines

We welcome submissions of original research papers (8 pages) as well as 
short papers (4-6 pages) focused on case studies, work-in-progress, or 
visionary ideas. All submissions must adhere to the AAAI author 
guidelines. Submissions should be made through the workshop's 
OpenReview.Net portal 
<https://openreview.net/group?id=AAAI.org/2025/Workshop/TIKA>. For any 
questions, please write to us at tika-2025 at googlegroups.com.


  Important Dates

Submission Deadline: November 24, 2024

Notification of Acceptance: December 9, 2024

Workshop Date: March 3-4, 2025


  Organizing Committee

Vinay Chaudhri (RelationalAI) - vchaudhri at acm.org

Chaitanya Baru (National Science Foundation) - cbaru at nsf.gov

Michael Genesereth (Stanford University) - genesereth at stanford.edu

Michael Witbrock (University of Auckland) - m.witbrock at auckland.ac.nz
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