AM talks about how whats in our working memory can affect how we think. For instance, the books I’m currently reading heavily influence my daily thoughts and project work. It might be necessarily a bad thing, but sometimes you notice some correlation due to availability rather than some deep truth.
It’s similar to that human need to create a story, or see narratives. For instance, I was reading ‘Zen and the Art..’ I viewed an uncertainty analysis as probing the ‘quality’ of model. This isn’t necessarily wrong but its not some objective definition for an uncertainty analysis, nor is it necessarily something unique (as in a new thought).
https://www.youtube.com/watch?v=OFuu4pesKf0
- AM uses the practice of making notes as he goes, getting comfortable with notation. This would be useful for probability study being conscious of the notation and comfortable with it.
- He also wants specific small tasks for himself as he goes as a form of reinforcement, I’d like to get more detail on what he means by this
- He defines questions, that can be returned to when you may have more knowledge. Kind of based on what the author is trying to get across, how they’re communicating the topic, wanting you to think.
- Approaching the reading of a book with some intent, what are you hoping to get from reading it? Are you trying to internalize the material? Map the topic landscape?
Research
try to think about the goal, the design, what are the aims?*
Want the code to:
- Be representation of the energy required in the core process of fuel production:
- Ability to alter uncertainty parameters at any level.
- Transparency on calculations run.
- Simplicity in the core model in that code should be built around some atomic LCA units.
- Ability to calculate all the energy of ‘fuel production’ to a known accuracy. So I have this now really.
New things keep popping up. Sometimes it feels like trying to establish some model, like the mass balance is the wrong move. Plugging in hard coded numbers with some wrapper might make more sense. Especially as the goal is directed towards modelling the energy at the moment.
I think it’s important to structure literature reading sessions around a problem to solve.
Some questions:
- For defining input distributions, choosing the sources, so Liam might be the expert to consult, or how do we derive
these.
- The central limit theorem might play a role here.
- What are common input parameter distributions (literature).
Chapter reread
Going to read through uncertainty chapter again with current model in mind.
Uncertainty might be difficult because it’s a form of probabilistic thinking which we don’t seem to be very good at. For a study, its hard to hold the ‘grey area’ in ones mind. You want to know what the result is. Taleb talks about this when you think about going to Paris or London for your holidays, you think about yourself in either of those places, not a 60% chance of being in Paris, 40% in London, mentally, its hard to fathom such an idea.
They like that definition of uncertainty that is:
everything we do not know.
I don’t know if I’m a fan of it. It’s very broad. Probability (according to Keynes) is relational. So we have a lack of knowledge about something not everything.
Does the central limit theorem mitigate the need to be too exact with the input parameter distributions? Each parameter would need to be considered identically distributed.
I think we’ll need to take into account model uncertainty.