3 papers
cs.LG2020
PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
Reinforcement learning (RL), particularly in sparse reward settings, often requires prohibitively large numbers of interactions with the environment, thereby limiting its applicabi…
cs.LG2019
Using Natural Language for Reward Shaping in Reinforcement Learning
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
Recent reinforcement learning (RL) approaches have shown strong performance in complex domains such as Atari games, but are often highly sample inefficient. A common approach to re…
cs.CV2016
End to End Learning for Self-Driving Cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski +10
We trained a convolutional neural network (CNN) to map raw pixels from a single front-facing camera directly to steering commands. This end-to-end approach proved surprisingly powe…