For the September 2 meeting at 8:00 pm EST.
Overall the research project is going very well, considering its difficulty.
Previously we've found some happy little bumps in the road. But recently we've discovered a large serious bump in the road, as described in the thread on Solving the problem of how to measure the truth. It's so large we need to all focus our efforts on solving it. Otherwise our project will probably fail.
This meeting is organized differently so we can focus our attention on the problem. Here's the agenda:
A. Discussion of solving the problem of how to measure the truth, with the goal of developing a plan of action.
B. Montserrat
C. Scott
D. Jack
Overall the research project is going very well, considering its difficulty.
Previously we've found some happy little bumps in the road. But recently we've discovered a large serious bump in the road, as described in the thread on Solving the problem of how to measure the truth. It's so large we need to all focus our efforts on solving it. Otherwise our project will probably fail.
This meeting is organized differently so we can focus our attention on the problem. Here's the agenda:
A. Discussion of solving the problem of how to measure the truth, with the goal of developing a plan of action.
- Please study the problem thread before the meeting, take notes, and develop your own thoughts on the problem.
- Do we all have the same definition of the problem? We take turns defining the problem in our own words.
- Is the problem well-structured? A well-structured problem is decomposed into the pieces that make up the problem in such a manner that makes getting started on analyzing the problem much easier. For example, SIP does this with a formal problem definition and by suggesting identifying the subproblems as the first step. Root cause analysis does this by suggesting a series of WHY questions as the first step. What I've done is structure the problem into subproblems to solve. These are the 6 categories of decisions. But is this good structure? Are other approaches possible?
- I'm beginning to suspect we have a missing abstraction(s). Tell story of what that term means, why so critical. What's missing is an abstraction that would tie our difficulties together with an insight explaining why we are having trouble and how it would be best to proceed, in a simple, elegant direction. One possibility for the missing abstraction is, for rule CLs between 0 and 100%, we are not using unified models of inductive logic. An example is the models discussed in this article on Inductive Logic. We don't need one model for everything. But we probably do need one model for each Spectrum Set type, as explained next.
- The crux of solving the truth measurement problem appears to be selecting the right rule with the right confidence level.
- Each rule should specify what inputs are needed.
- The inputs are a much easier part of the problem to solve, like setting fact CLs and selecting the right facts and reusable claims.
- Presently the rules tree has 4 main container folders: Fallacies, Non-fallacies, Opposite Pairs, and Spectrum Sets. The first 3 have zero or 100% CLS in their rules. These are not a big problem. The problem lies in the Spectrum Sets that do not deal with statistical certainty. These are the inconsistent and consistent evidence leaf folders. These contain rule CLs between 0 and 100% , like 5% and 20%.
- Click on the Evidence - Inconsistent folder. Study its description. That's a start on how to make selecting the right rule with the right CL easy and correct. The 0% CL rule selection criteria looks okay. (?) But the others look weak. The result will be low precision, which means high variability across claim-checks. How can we improve the criteria? This is exactly where I'm stuck right now. It may be this needs a formal model behind it.
- Once we have solved the weak selection problem of the Evidence - Inconsistent folder, we can probably use that solution on the Evidence - Consistent folder.
- Once we've solved the above two problems, we can then look at the 6 categories of decisions and attempt to solve all of them. I suspect that task will be much easier once we've solved the "selecting the right rule with the right confidence level" problem.
- This problem is an area Scott Collison may be able to help in.
- Any other thoughts on solving the problem of how to measure the truth?
B. Montserrat
- Research project report. This is the 6th report. The areas of the report are:
- Risk status.
- Is it possible we are too focused on details, and are missing some higher level risks or priorities?
- Schedule status.
- What about the impact of the above problem on the schedule?
- Help needed in upcoming week.
- Work focus and central challenges for the upcoming week.
- Discussion as needed.
- Risk status.
- Comments on her first claim check.
- Comments on her trip to take the scholarship test.
- Anything else?
C. Scott
- Any topics here?
D. Jack
- Good news. The software is stable, complete enough, and is now taking only about 20% of my time.
- I'm expecting to be working with Scott Collison soon.
- I'm focusing on the problem of how to measure the truth.
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