This will be a joint session together with the DIP Colloquium.
Speaker: Igor Douven (IHPST/CNRS/Panthéon Sorbonne University)
Date and Time: Thursday, October 24th 2024, 16:30-18:00
Venue: KdVI seminar room F3.20 in Science Park 107
Title: Reinforcement Learning as Meta-induction
Abstract : The meta-inductive justification of induction is usually regarded as a social learning strategy. But, pre-theoretically, induction can be justified even for an isolated thinker, incapable of, or unwilling to engage in, any social interactions. This paper presents reinforcement learning (RL) as a natural meta-inductive strategy for such isolated thinkers. The meta-inductive reinforcement learner learns to choose an optimal prediction method among the available methods by applying trial and error learning. We use computer simulations to show that, under plausible assumptions, trial and error learning indeed leads the thinker to favor induction over non-inductive predictive methods. Under further plausible assumptions, the meta-inductive thinker itself is even seen to outperform all object-level methods. The results are shown to hold true in both stationary and non-stationary environments.
(This is joint work with Gerhard Schurz.)