Meta-RL with Bayesian Linear Task Models
GLiBRL, a deep Bayesian RL framework that combines generalised linear task models with learnable non-linear basis functions, features conjugate Bayesian inference, yielding exact, sequential posterior updates over task parameters and model noise, together with a closed-form marginal likelihood that eliminates variation...