I recently left OpenAI to pursue independent research. I’m working on a number of different research directions, but they’re unified by the core idea of a scale-free theory of intelligent agency. In this post I give a rough sketch of how I’m thinking about that. I’m erring on the side of sharing half-formed ideas, so there may well be parts that don’t make sense yet. Nevertheless, I think this broad research direction is very promising.

This post has two sections. The first describes what I mean by a theory of intelligent agency, and some problems with existing (non-scale-free) attempts. The second outlines my current path towards formulating a scale-free theory of intelligent agency, which I’m calling coalitional agency.

Theories of intelligent agency

By a “theory of intelligent agency” I mean a unified mathematical framework that describes both understanding the world and influencing the world. In this section I’ll [...]

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Outline:

(00:56) Theories of intelligent agency

(01:23) Expected utility maximization

(03:36) Active inference

(06:30) Towards a scale-free unification

(08:48) Two paths towards a theory of coalitional agency

(09:54) From EUM to coalitional agency

(10:20) Aggregating into EUMs is very inflexible

(12:38) Coalitional agents are incentive-compatible decision procedures

(15:18) Which incentive-compatible decision procedure?

(17:57) From active inference to coalitional agency

(19:06) Predicting observations via prediction markets

(20:11) Choosing actions via auctions

(21:32) Aggregating values via voting

(23:23) Putting it all together

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Narrated by TYPE III AUDIO.

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