First-order logic is necessary and sufficient to specify any and every program that runs on a digital computer. But OWL 2 is limited, quirky, and far more difficult to learn and use that FOL.
Recommendation: Design OWL 3 as exactly compatible with the OWL 2 hierarchy, but replace Turtle or other notations for the constraint language with an easy to read, write, and remember version of FOL. For upward compatibility, keep all the OWL 2 features and syntax as an option which shall remain available in all future upgrades to OWL 3.
Syntax for the OWL 3 constraint language: The reserved words and phrases that are used to represent constraints: Some; Every; and; or; not; if... then,,,; only if; if and only if.
Every statement in the constraint language shall be a syntactically correct English sentence, which uses the reserved words above plus whatever words or symbols anybody chooses to represents entities in the subject domain.
Result: Statements in the constraint language may be read without any training by anybody who can read English. Learning to write the constraint language will require much less training than learning to write anything in OWL 2.
Observation: The very intelligent logicians who designed OWL 1 and 2, made an incorrect assumption about issues of decidability.
(1) undecidable statements are very complex, and nobody but a highly trained and knowledgeable logician would know how to write one,; 99.99% of software developers would not know how to read or write such a statement.
(2) Undecidable statements only cause a problem for a theorem prover; they would NEVER cause any problem if and when they are used to state a constraint and use a constraint.
(3) But the syntactic constraints to prevent undecidable statements cause Turtle and other notations to become far more complex, unreadable, and unwritable than pure simple FOL expressed as English sentences,
(4) For authors who do not read or write English, it's easy to specify exactly equivalent versions in every language spoken at the United Nations. Every one of those versions would have a simple and efficient translation to the English version.
John
**apologies for cross-posting**
The HHAI 2025 Doctoral Consortium (DC) will take place as part of the 4th
International Conference on Hybrid Human-Artificial Intelligence in June
2025, Pisa, Italy: https://hhai-conference.org/2025/
This forum will provide early as well as middle/late-stage PhD students in
the field of Hybrid Intelligence focusing on the study of Artificial
Intelligence systems that cooperate synergistically, proactively and
purposefully with humans, amplifying instead of replacing human
intelligence. The Doctoral Consortium will take place in person at the HHAI
2025 conference.
The DC provides an opportunity to present and discuss their doctoral
research ideas and progress in a supportive, formative and yet critical
environment and receive feedback from reviewers, mentors and peers from the
field of Hybrid Intelligence. The Doctoral Consortium will also provide
opportunities to network and build collaborations with other members of the
HHAI community. We welcome submissions across research HHAI-related domains
such as AI, HCI, cognitive and social sciences, philosophy & ethics,
complex systems, and others (see “Topics of interest”).
The event is intended for early as well as middle/late-stage PhD candidates
and asks them to formulate and submit a concrete PhD research proposal,
preferably supported by some preliminary results. The proposal will be
peer-reviewed. If accepted, students must register and physically attend
the event, which will include a range of interactive activities (among
which presentations and mentoring lunch). Details for the submission are
found below under “Submission Details”.
**Important Dates**
Submission Deadline: January 24, 2024
Reviews Released: March 18, 2025
Camera-ready Papers: April 13, 2025
Doctoral Consortium: June 10, 2025
All deadlines are 23:59 AoE (anywhere on Earth)
**Topics of Interest**
We invite research on different challenges in Hybrid Human-Artificial
Intelligence. The following list of topics is illustrative, not exhaustive:
• Human-AI interaction, interpretation and collaboration
• Adaptive human-AI co-learning and co-creation
• Learning, reasoning and planning with humans and machines
in the loop
• User modeling and personalisation
• Integration of learning and reasoning
• Transparent, explainable, and accountable AI
• Fair, ethical, responsible, and trustworthy AI
• Societal awareness of AI
• Multimodal machine perception of real-world settings
• Social signal processing
• Representations learning for Communicative or Collaborative
AI
• Symbolic representations for human-centric AI
• Human-AI Coevolution
• Foundation models and humans
• Human cognition-aware AI
• Decentralized human-AI systems
• Reliability and robustness in human-AI systems
• Applications of hybrid human-AI intelligence
**Submission Details**
All proposals must be submitted electronically via the EasyChair conference
submission system: https://easychair.org/my/conference?conf=hhai2025. Each
PhD student should provide the following information on Easychair:
• Research proposal (details below).
• Supplementary material: a maximum of 2-page PDF listing the
following:
• Names and affiliations of your research supervisor(s).
• Dissertation status: When you began your PhD, and expected
to complete it. Are there any constraints on the PhD duration from your
institute? This part helps us better tailor feedback to a realistic
timeline according to your program.
• Benefits statement: 1-2 paragraphs describing what you hope
to gain by participating in the doctoral consortium. Highlight specific
points where you require feedback.
• A personal statement citing three key papers in the field
and briefly describing how they influenced the student’s work and how HHAI
is defined in those works and the student’s research.
• List of the student’s relevant publications (if available).
**Research Proposal Details**
Students should submit a maximum of a 6-page description of their PhD
research proposal. Papers should be written in English and adhere to IOS
formatting guidelines. The limit of 6 pages is excluding references.
The papers should have a single author (the PhD candidate) and submissions
are *not* anonymous. Supervisors, other involved persons, and funding
agencies should be acknowledged in an Acknowledgements section.
Research proposals should contain the following elements:
• Context: The background and motivation for your research,
including the related work that frames your research
• Research questions/challenges: what are the research
questions/challenges that your dissertation addresses? Try to highlight how
it differs from existing literature.
• Method/approach and evaluation: how is each of the research
questions answered? How are results evaluated? If you are planning to
conduct studies or build prototypes, provide a brief description.
• Preliminary results (if available). Highlight results and
contribution to date and the timeplan for projected steps.
• Discussion and future work: What are intermediary
conclusions, and what are the planned next steps?
**Upon Acceptance of the Doctoral Consortium Proposal**
Accepted papers will be published in the main conference proceedings of the
Third International Conference on Hybrid Human-Machine Intelligence, in the
Frontiers in AI and Applications (FAIA) series by IOS Press. Authors will
have the opportunity to opt-out from being included in these proceedings,
with only their proposal title being mentioned on the web page.
Participants will be expected to give short, informal presentations of
their work during the consortium, to be followed by a discussion.
In case there are any questions regarding the call, or if you are unsure
about submitting your work to the HHAI 2025 Doctoral Consortium, please
reach out to dc(a)hhai-conference.org
**DC Chairs**
Jennifer Renoux (Örebro University)
Salvatore Ruggieri (University of Pisa)
Stefan Schlobach (Vrije Universiteit Amsterdam)
Shihan Wang (Utrecht University)