Structure of Intelligence

Intelligence is a solution to the problem of adapting across diverse environments. Fields like learning theory, computational complexity theory, game theory, and social choice theory each study what is theoretically possible for intelligent agents in certain contexts under specific sets of constraints (information, computation, trust, etc.).

But some rich structures of intelligent systems only emerge when these constraints are combined. I believe there are low-hanging fruits to be found in taking underconstrained and the overly-abstracted models often used in these settings, and trying to give them flesh.

Questions this project seeks to answer:

• What is the proper theoretic framework for jointly addressing the computational and informational limitations of intelligent systems?
• What are toy problems which capture the need for inference-time computation/search for a jointly informationally and computationally efficient learner?
• How to intelligent systems bias their search processes toward solutions with verifiable structure?
• When does verifiability stand at cross purposes to capability?

Status: Active

Linked Posts:

• What Is Thinking?