16 citations · 18 across the 5 of their papers we have counts for
3 papers · 1 filter
AnyMorph: Learning Transferable Polices By Inferring Agent Morphology
Brandon Trabucco, Mariano Phielipp, Glen Berseth
The prototypical approach to reinforcement learning involves training policies tailored to a particular agent from scratch for every new morphology. Recent work aims to eliminate t…
Synthetic Datasets for Neural Program Synthesis
Richard Shin, Neel Kant, Kavi Gupta +4
The goal of program synthesis is to automatically generate programs in a particular language from corresponding specifications, e.g. input-output behavior. Many current approaches…
Inferring the Optimal Policy using Markov Chain Monte Carlo
Brandon Trabucco, Albert Qu, Simon Li +1
This paper investigates methods for estimating the optimal stochastic control policy for a Markov Decision Process with unknown transition dynamics and an unknown reward function.…