Hi, I’m Vardhan, one of the Dovetail fellows this winter. Thanks Alex & Alfred for running this!
Background: I study mathematics and computer science (probability, algorithms, game theory) and I’m interested in formal models of agents and multi-agent interaction.
For the fellowship, I looked at the question: Which agents can be faithfully described by finite automata / finite transducers, and which structural properties make that more or less likely? In other words, when can an agent’s externally observable behavior be captured by a finite (possibly stochastic) automaton, and what observable signatures indicate that a finite-state model is impossible or misleading?
I’ve written a brief report summarizing definitions, toy examples, and some light lemmas. I’m planning a longer post with formal definitions, more examples, and proofs. I’d really appreciate recommendations on literature I may have missed (especially anything linking automata/dynamical-systems perspectives to algorithmic information theory, ergodic theory, or learning theory). Comments, questions, and pointers very welcome!
Hi, I’m Vardhan, one of the Dovetail fellows this winter. Thanks Alex & Alfred for running this!
Background: I study mathematics and computer science (probability, algorithms, game theory) and I’m interested in formal models of agents and multi-agent interaction.
For the fellowship, I looked at the question: Which agents can be faithfully described by finite automata / finite transducers, and which structural properties make that more or less likely? In other words, when can an agent’s externally observable behavior be captured by a finite (possibly stochastic) automaton, and what observable signatures indicate that a finite-state model is impossible or misleading?
I’ve written a brief report summarizing definitions, toy examples, and some light lemmas. I’m planning a longer post with formal definitions, more examples, and proofs. I’d really appreciate recommendations on literature I may have missed (especially anything linking automata/dynamical-systems perspectives to algorithmic information theory, ergodic theory, or learning theory). Comments, questions, and pointers very welcome!