Knowledge Enhanced Electronic Logic (KEEL
Frequently Asked Questions
This page documents some questions that have been received by Compsim from companies interested in getting a better understanding of KEEL Technology.
Why do you consider KEEL a "disruptive technology"?
Why do you suggest that KEEL Technology is a form of AI (Artificial Intelligence)? And why do you suggest it might be a "better" form of AI?
Why do you call KEEL Technology a form of “Explainable AI”?
What is the "underlying technology" that defines KEEL?
Why do you differentiate Rules from Judgment?
Is KEEL more than an analog computer?
How does KEEL differ from Fuzzy Logic?
How does KEEL differ from Neural Nets?
How does KEEL compare to Machine Learning?
How does KEEL compare to tensor-based machine learning?
How does KEEL compare to Neuromorphic Engineering or Neuromorphic Computing?
How does KEEL Technology differ from Agent Technology?
How would you compare KEEL to probability based solutions (Bayesian / Markov / etc.)?
How does KEEL differ from conventional AI Expert Systems?
How does KEEL differ from conventional Rule-Based Systems?
How does KEEL differ from scripted AI languages like CLIPS?
Why don't you include a database in the KEEL Engine?
Why do you suggest there is a different "mindset" for the developer?
Why do you say that with KEEL, you tell machines "how to think" and how does this differ from "supervised machine learning", or "deep learning"?
How does KEEL compare to curve fitting approaches?
Does KEEL learn?
How do you differentiate "adapting" from "learning" (a machine that adapts, versus a machine that learns how to perform), and why should you care?
Is KEEL scalable?
Is KEEL suitable for upgrading existing systems, or only for integration into new systems?
How can you model physical systems with KEEL?
Why do you call KEEL a "technology" rather than "tool"?
What do you do if your domain experts don't think in curves?
What do you do if there is more than one expert and they disagree?
How can you use KEEL if you don't know what the outputs and inputs are?
How are the concepts of "surprise" and "missing information" handled by KEEL Technology?
Isn't the KEEL graphical language just another way to create a formula?
How does the KEEL graphical language differ from other "graphical languages"?
How does your "tool" compare to "LabVIEW" (National Instruments) or other similar HMI tools?
What types of problems are best suited for a KEEL solution?
What are some examples of "behavior", when you say that KEEL can be used to model "behavior"?
How might KEEL be used to represent or model
How might KEEL be used to provide ethical behavior to autonomous systems (robotic ethics)?
How does bias impact KEEL Models?
How do you include emotions and morality into a KEEL Model?
How do you handle the situation when one piece of information comes in slightly before another piece of information?
How does KEEL work in a collaborative environment?
Why do you call KEEL a new form of mathematics?
What are some examples of curves / non-linear relationships that can be defined and executed with KEEL?
You say a KEEL system is made of inter-related curves. How does one tie all the curves together?
Can KEEL be used in "planning"?
Is KEEL deterministic?
Do you / How do you handle temporal data?
Does KEEL require assigning weights to input variables?
How does KEEL address probabilistic fuzzy problems?
What do you mean by a "small memory footprint"?
What processors can you target?
What "language" was used to create the KEEL "tools"?
How easy is it to integrate KEEL Technology into an existing application?
Why is licensing KEEL different than licensing a software tool like Microsoft Excel?
Have you studied Tverskyi's paper, Gestalt psychology, Plato and all the others that have written extensively on decision-making in order to validate the KEEL decision-making model?
Why do you use the Left-Brain / Right-Brain paradigm to explain KEEL when this particular comparison has been called a "psychology myth"?
Who are your competitors (for KEEL)?
What do I need to know to create KEEL-based solutions (to prepare for KEEL)?
How long does it take to learn how to audit the behavior of a KEEL-based system? And how is this accomplished?
What technical skills are necessary to learn KEEL Technology in order to create KEEL-based cognitive engine components that can be inserted into devices or software applications?
What do you mean by "Adversarial Systems"? And how does KEEL Technology play in the Adversarial Computing domain?
What factors do you consider important in Adversarial Computing / Adversarial Systems, and how does KEEL Technology respond to those demands?
Why do you suggest that KEEL Technology provides a new way to allow humans to influence the behavior of Autonomous Systems without full remote control, and why might this be better than conventional remote control?
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