9 citations · 14 across the 5 of their papers we have counts for
4 papers · 1 filter
Better Safe than Sorry: Evidence Accumulation Allows for Safe Reinforcement Learning
Akshat Agarwal, Abhinau Kumar, Kyle Dunovan +3
In the real world, agents often have to operate in situations with incomplete information, limited sensing capabilities, and inherently stochastic environments, making individual o…
Challenges of Context and Time in Reinforcement Learning: Introducing Space Fortress as a Benchmark
Akshat Agarwal, Ryan Hope, Katia Sycara
Research in deep reinforcement learning (RL) has coalesced around improving performance on benchmarks like the Arcade Learning Environment. However, these benchmarks conspicuously…
Community Regularization of Visually-Grounded Dialog
Akshat Agarwal, Swaminathan Gurumurthy, Vasu Sharma +2
The task of conducting visually grounded dialog involves learning goal-oriented cooperative dialog between autonomous agents who exchange information about a scene through several…
Learning Time-Sensitive Strategies in Space Fortress
Akshat Agarwal, Ryan Hope, Katia Sycara
Although there has been remarkable progress and impressive performance on reinforcement learning (RL) on Atari games, there are many problems with challenging characteristics that…