- #ORF09 An introduction to the RETE algorithm
- #ORF09 Playing With the Rules Presentation
- #ORF09 Rule Patterns and Features Presentation
- #ORF09 Early Alert System Presentation
- #ORF09 Engineer’s perspective on Rule Technology Keynote
- #ORF09 Enterprise Architecture Presentation
- #ORF09 Enterprise Architecture Presentation Part II
- #ORF09 Model Driven Approach for BRMS Presentation
- #ORF09 Production Rule Systems
- #ORF09 Graph Based Knowledge Bases and Rules Presentation
- #ORF09 Truth versus Useful Lies Presentation
- #ORF09 Automated Verification of rules Presentation
- #ORF09 Agile Business Rule Development Presentation
- #ORF09 Rule Classification First Presentation
- #ORF09 Rule Violation and Over-Constrained Problems Presentation
- #ORF09 Generating Rules from UML presentation
- #ORF09 What’s Different about Rules in CEP Presentation
- #ORF09 Measuring your Rules’ KPI Presentation
- #ORF09 Designing a System of Rule Based Agents Presentation
- #ORF09 Extending General Purpose Engines Presentation
- #ORF09 Programming Rules using a spreadsheet interface
- #ORF09 Practical and Modern RBE Presentation
- #ORF09 Temporal Reasoning Presentation
- #ORF09 Business Rules in the Cloud Presentation
- #ORF09 October Rules Fest Think Tank
- #ORF09 October Rules Fest Think Tank – Part II
- #ORF09 CLIPS implementation of RETE Presentation
- #ORF09 Complex Event Processing Models Presentation
- #ORF09 Distributed Programming with Agents Presentation
- #ORF09 making Parallelism Available to Rule Developers Presentation
Dr. Daniel S. Levine is talking about how the brain works. His work is in human psychology, and he hopes that some of this knowledge can be useful for knowledge based systems.
Our memory can play tricks on us by creating information that was not there in the first place because other information “suggests” it.
Children or novices store and remember things literally. Adults or experts store and remember as “gists”. The passage from verbatim to gists will happen with the familiarity of the subject and with the development of cognitive capacities such as analogy.
The gists will create some challenges because sometimes the wrong gist is remembered (or encoded). Gists are required to understand trends and to see analogies. Verbatim is needed to override inaccuracies.
We can override our learned gist rules and we can follow those rules. We can be automatic or controlled; deliberate or heuristic; gist or verbatim. People will shift their level of representation (task calibration) based on some different factors.
How can rule systems adapt their level of representation based on the goal? We have not solved that problem yet. How do you decide which level or representation that you need to resolve that problem?
He ends his talk on that note, indicating that they are working on understanding task calibration better so that one day it can maybe applied to knowledge systems.
Tags: Business Rules, Conferences, ORF09




