I use computational models to study how philosophically puzzling aspects of our epistemic and social lives might arise from natural selective processes like reinforcement learning and Darwinian evolution. On the epistemic side, I am interested broadly in the evolution of inductive practice, with a special focus on issues of projectibility. On the social side, I am most interested in the emergence of other-regarding preferences. At the intersection of the two, I am interested in how groups of inquirers might come to exercise epistemic powers possessed by none of their members individually.
[6] Egalitarianism and Evolution (2026)
Theory and Decision
python code for learning model // python code for population model
uses the indirect evolutionary approach to model the evolution of a taste for equality in a bargaining game
[5] Task-Switching and Natural Projectibility (2026)
Synthese
articulates a version of Goodman's "new riddle of induction" that applies generally to learners in nature; develops a model showing how that problem might be solved by means of a simple form of reinforcement learning in the context of an experiment on task-switching in rhesus macaques
[4] Learning in Crawford-Sobel Games (2025)
with Jeff Barrett, Cailin O'Connor, and Brian Skyrms, forthcoming in British Journal for the Philosophy of Science
bridges a gap in the game theoretic literatures on communication in philosophy and economics by modeling simple forms of trial-and-error learning in Crawford-Sobel games and comparing findings to related results for Lewis-Skyrms signaling games
[3] Learning to Forget (2025)
with Jeff Barrett, forthcoming in British Journal for the Philosophy of Science
considers how reinforcement learners in Lewis-Skyrms signaling games might learn to adopt methods of learning well-adapted to the communicative problems they repeatedly face
[2] Learning How to Learn by Self-tuning Reinforcement (2024)
 with Jeff Barrett, Synthese
develops a model of self-tuning reinforcement learning that captures a well-known experimental finding on learning to learn in rhesus macaques
[1] Janina Hosiasson and the Value of Evidence (2024)
Studies in History and Philosophy of Science
shows that I.J. Good's classic result concerning the pragmatic value of learning is prefigured in a 1931 paper by Janina Hosiasson
A paper on Alexander Bain's theory of learning
draft available on request
A paper on category learning in signaling games
draft available on request
A paper on learning laws of nature
with Jeff Barrett
A paper on belief aggregation in epistemic networks
in preparation