John Sowa and Arun Majumdar at the Ontology Summit

[Ken Baclawski]

Ontology Summit 2026
Ontologies: Past, Present, Future

We are very pleased to announce that the next Ontology Summit session on Wednesday 3 June 2026 will feature

Arun K. Majumdar and John F. Sowa

who will present

Reasoning Beats Pattern Matching

As usual, all summit sessions are zoom sessions on Wednesdays at Noon US/Canada Eastern Time and each session lasts one hour.  The summit is open to the public and no registration is necessary.  All summit sessions are recorded and are available on the summit web pages and on the Ontology Summit YouTube channel.

The session page is: https://ontologforum.com/index.php/ConferenceCall_2026_06_03

Zoom information:

https://us02web.zoom.us/j/86994661673?pwd=mMUeaWyWhBMSzTw3SgH5GjMv2Qx4rH.1
Meeting ID: 869 9466 1673
Passcode: 803090

Abstract: For over 60 years, the best AI reasoning was based on the four step cognitive cycle:  abduction, deduction, evaluation, induction, and repeat.  Abduction generates hypotheses or educated guesses.  Deduction derives implications.  Evaluation chooses the best option.  Induction combies the result with previous knowledge.

Many versions of the cognitive cycle have been invented and named. For guiding fighter pilots, John Boyd called it the OODA loop: Observe, Orient, Decide, Act.  He originally said that each step would be traversed in milliseconds, but he later applied the loop to design and analysis steps that may take minutes, hours, or days.  Whatever the time scale, the four steps are fundamental to reasoning in science, business, and life.

The pattern matching methods of Large Language Models (LLMs) are superb for translating languages, natural or artificial. They are also good for finding and relating patterns in large volumes of data of any kind. That enables them to answer questions by finding information or by applying previous methods to new data.  For many problems, pattern matching can discover abductions or educated guesses.  But deduction and evaluation cannot be done unless a similar cognitive cycle can be found somewhere on the WWW.

With the VivoMind system from 2000 to 2010, the authors used conceptual graphs for  symbolic reasoning about a wide range of problems. For the new Permion system, they added LLM pattern matching to map conceptual graphs to and from natural language.  But pattern matching, by itself, cannot do any reasoning unless it can find and adapt an appropriate cycle on the WWW.  It often requires a huge amount of searching even for relatively simple examples.

In summary, LLMs cannot do reasoning unless and until the system finds a suitable cognitive cycle on the WWW.  But the Permion reasoning methods automatically do the four-step cycle. If necessary, they can also do LLM searching, but none is required.

Ken Baclawski
Chair, Ontology Summit 2026