[snasan]

All these mental models are simplified maps of an infinitely complex reality. When we rely on them too heavily, do we risk falling into the trap of mistaking the map for the actual territory? The very tools we use to understand the world can end up shaping and even limiting our perspective. That's why being aware of the limitations of the models themselves is just as important as using them.

[iammjm]

“All perception is gamble” - Robert Anton Wilson / Husserl

[rodolphoarruda]

From the same website.

https://fs.blog/map-and-territory/

[DonHopkins]

Your map/territory risk is exactly what this lineage formalizes -- internal maps are necessary but they shape and limit perception. Walter Lippmann (1922) makes "pictures in our heads" the operative reality of public judgment:

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...