Yeah yeah, like someone is doing charity here.
Will always be grateful to Shane for that!
Shane's mental models books are packed with a lot of random/disparate domains/insights -- He's a good aggregator there.
Thinking in Systems by Meadows.
Really, once you go down the rabbit hole, you find new threads to pull. That's kind of the fun of it
https://en.wikipedia.org/wiki/Public_Opinion
Frederic Bartlett (1932) defines schemas as memory structures that pre-shape perception and recall:
https://en.wikipedia.org/wiki/Schema_(psychology)
Jean Piaget explains schema updating via assimilation/accommodation when evidence conflicts with the map:
https://en.wikipedia.org/wiki/Assimilation_(psychology)
Edward Tolman introduces cognitive maps, making "map" literal in psychology:
https://en.wikipedia.org/wiki/Cognitive_map
Marvin Minsky formalizes frames as slot-filled expectations that speed inference but can blind you to anomalies:
https://en.wikipedia.org/wiki/Frame_(artificial_intelligence...
voidhorse: "mental model" vs "theory" is a real distinction in the literature. Kenneth Craik frames small-scale models as internal simulations for reasoning, not public theories:
https://en.wikipedia.org/wiki/Kenneth_Craik
Philip Johnson-Laird formalizes mental models as internal simulations used for inference and prediction:
https://en.wikipedia.org/wiki/Philip_Johnson-Laird
andsoitis: "informal, simplified, personal" models are exactly why systematic errors show up. Daniel Kahneman and Amos Tversky document heuristics and biases when internal maps are over-trusted:
https://en.wikipedia.org/wiki/Heuristics_in_judgment_and_dec...
Repair loop: Seymour Papert's microworlds provide controlled sandboxes for testing and revising models:
https://en.wikipedia.org/wiki/Constructionism_(learning_theo...
Gary Drescher gives a schema mechanism for incremental action/outcome updates that rebuild the map from experience:
https://mitpress.mit.edu/9780262517089/made-up-minds/
If you want to see Drescher operationalized, MOOLLM turns the schema mechanism into working skills. Schema Mechanism is the causal core, Schema Factory adds a deterministic toolchain and context bundles for LLM reasoning, and Play-Learn-Lift is the governance loop that maps ACT/OBSERVE/ATTRIBUTE/SPIN OFF into audited upgrades. This is GOFAI made practical with LLMs filling the old gaps in grounding and explanation.
Drescher's Schema Mechanism as Anthropic Skill:
https://github.com/SimHacker/moollm/blob/main/skills/schema-...
Drescher's Schema Factory as Anthropic Skill:
https://github.com/SimHacker/moollm/blob/main/skills/schema-...
Play=>Learn=>Lift methodology as Anthropic Skill:
https://github.com/SimHacker/moollm/blob/main/skills/play-le...
Here is the exact kind of thing we are talking about -- the YAML Jazz schema examples are live, readable schemas-by-example with causal context, semantic comments, evidence counts, side effects, and marginal attribution notes, including a practical devops edgebox/ingest cluster and a Zork/MUD "learn by dying" cluster so you can see the mechanism at work in real data:
https://github.com/SimHacker/moollm/blob/main/skills/schema-...
# YAML Jazz schema examples (comments are semantic)
#
# These are schemas-by-example: minimal structure, rich intent.
# Follow canon schema rules where possible, but annotate as needed.
# Ad hoc fields and side-notes are allowed for partially jelled ideas.
And here is a MOOLLM simulation session explaining Gary Drescher's ideas themselves -- an ethical tribute simulation (not actually real people), grounded in documented work and analyzed source code, and framed for a simulated audience of familiar experts, to show how a Society of Mind meets "The Sims" style ensemble can explain itself:https://github.com/SimHacker/moollm/blob/main/examples/adven...
Finally, if you want the deeper connections tour written specifically for this thread -- the big-picture synthesis that ties Papert, Minsky, Drescher, Play-Learn-Lift, and live microworlds into one operational map -- dive here:
https://github.com/SimHacker/moollm/blob/main/designs/CONNEC...
There's an argument to be made that it is useful to distinguish between mental models and theories.
If a theory is a structured, formal explanation of phenomena, grounded in evidence, logic, and often mathematics that is meant to be shared, tested, and and falsified, a mental model is more of an internal representation of how something works, often informal, simplified, personal, and built to help you reason, predict, and decide.
I find both tools useful, but different.
But what I really wanted to say, this reminds me of Scott E Page’s Coursera course on Model Thinking, and a book: “The Model Thinker What You Need to Know to Make Data Work for You” also from 2018.
A transcript of Charlie's speech is still up https://fs.blog/great-talks/a-lesson-on-worldly-wisdom/
I guess Shane Parrish is trying to carry the torch on now that Charlie has passed.
That said, I am on mobile…?
hahahacorn•2w ago
Always a good read
dang•2w ago
Mental Models: The Best Way to Make Intelligent Decisions - https://news.ycombinator.com/item?id=24527003 - Sept 2020 (35 comments)
Mental Models: The Best Way to Make Intelligent Decisions (113 Models Explained) - https://news.ycombinator.com/item?id=17121145 - May 2018 (36 comments)
dullcrisp•2w ago
You can use the Wayback Machine to read the version that was originally discussed.
evrydayhustling•2w ago