Executive summary: Paradigm formation in mathematical fields like chaos theory and agent foundations differs from scientific paradigms, focusing more on resolving conceptual confusion than predicting empirical phenomena.
Key points:
Paradigms in math-like fields are sets of methods for solving problems, rather than frameworks for predicting reality.
Chaos theory may unify understanding across diverse systems (e.g., weather, eye movement), similar to plate tectonics in geology.
Agent foundations seeks a formal characterization of agency, analogous to Turing machines defining “effective methods” in computation.
Mathematical paradigms like Turing machines or Shannon’s information theory resolve confusion and enable progress without directly predicting phenomena.
The usefulness of chaos theory for improving predictions (e.g., in weather forecasting) remains uncertain and worthy of further investigation.
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Executive summary: Paradigm formation in mathematical fields like chaos theory and agent foundations differs from scientific paradigms, focusing more on resolving conceptual confusion than predicting empirical phenomena.
Key points:
Paradigms in math-like fields are sets of methods for solving problems, rather than frameworks for predicting reality.
Chaos theory may unify understanding across diverse systems (e.g., weather, eye movement), similar to plate tectonics in geology.
Agent foundations seeks a formal characterization of agency, analogous to Turing machines defining “effective methods” in computation.
Mathematical paradigms like Turing machines or Shannon’s information theory resolve confusion and enable progress without directly predicting phenomena.
The usefulness of chaos theory for improving predictions (e.g., in weather forecasting) remains uncertain and worthy of further investigation.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.