Knowledge Enhanced Electronic Logic (KEEL®)

Also check PAPERS for additional information.

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.

  1. Why do you consider KEEL a "disruptive technology"?
  2. What is the "underlying technology" that defines KEEL?
  3. Why do you differentiate Rules from Judgment?
  4. Is KEEL more than an analog computer?
  5. How does KEEL differ from Fuzzy Logic?
  6. How does KEEL differ from Neural Nets?
  7. How does KEEL compare to Neuromorphic Engineering or Neuromorphic Computing?
  8. How does KEEL Technology differ from Agent Technology?
  9. How would you compare KEEL to probability based solutions (Bayesian / Markov / etc.)?
  10. How does KEEL differ from conventional AI Expert Systems?
  11. How does KEEL differ from conventional Rule-Based Systems?
  12. How does KEEL differ from scripted AI languages like CLIPS?
  13. Why don't you include a database in the KEEL Engine?
  14. Why do you suggest there is a different "mindset" for the developer?
  15. How does KEEL compare to curve fitting approaches?
  16. Does KEEL learn?
  17. Is KEEL scalable?
  18. Is KEEL suitable for upgrading existing systems, or only for integration into new systems?
  19. How can you model physical systems with KEEL?
  20. Why do you call KEEL a "technology" rather than "tool"?
  21. What do you do if your domain experts don't think in curves?
  22. What do you do if there is more than one expert and they disagree?
  23. How can you use KEEL if you don't know what the outputs and inputs are?
  24. How are the concepts of "surprise" and "missing information" handled by KEEL Technology?
  25. Isn't the KEEL graphical language just another way to create a formula?
  26. How does the KEEL graphical language differ from other "graphical languages"?
  27. How does your "tool" compare to "LabVIEW" (National Instruments) or other similar HMI tools?
  28. What types of problems are best suited for a KEEL solution?
  29. What are some examples of "behavior", when you say that KEEL can be used to model "behavior"?
  30. How might KEEL be used to represent or model emergent behavior?
  31. How might KEEL be used to provide ethical behavior to autonomous systems (robotic ethics)?
  32. How do you handle the situation when one piece of information comes in slightly before another piece of information?
  33. How does KEEL work in a collaborative environment?
  34. Why do you call KEEL a new form of mathematics?
  35. What are some examples of curves / non-linear relationships that can be defined and executed with KEEL?
  36. You say a KEEL system is made of inter-related curves. How does one tie all the curves together?
  37. Can KEEL be used in "planning"?
  38. Is KEEL deterministic?
  39. Do you / How do you handle temporal data?
  40. Does KEEL require assigning weights to input variables?
  41. How does KEEL address probabilistic fuzzy problems?
  42. What do you mean by a "small memory footprint"?
  43. What processors can you target?
  44. What "language" was used to create the KEEL "tools"?
  45. How easy is it to integrate KEEL Technology into an existing application?
  46. Why is licensing KEEL different than licensing a software tool like Microsoft Excel?
  47. 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?
  48. Why do you use the Left-Brain / Right-Brain paradigm to explain KEEL when this particular comparison has been called a "psychology myth"?
  49. Who are your competitors (for KEEL)?
  50. What do I need to know to create KEEL-based solutions (to prepare for KEEL)?