2 citations · 3 across the 2 of their papers we have counts for
3 papers · 1 filter
Position: Benchmarking is Limited in Reinforcement Learning Research
Scott M. Jordan, Adam White, Bruno Castro da Silva +2
Novel reinforcement learning algorithms, or improvements on existing ones, are commonly justified by evaluating their performance on benchmark environments and are compared to an e…
From Past to Future: Rethinking Eligibility Traces
Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari +3
In this paper, we introduce a fresh perspective on the challenges of credit assignment and policy evaluation. First, we delve into the nuances of eligibility traces and explore ins…
Behavior Alignment via Reward Function Optimization
Dhawal Gupta, Yash Chandak, Scott M. Jordan +2
Designing reward functions for efficiently guiding reinforcement learning (RL) agents toward specific behaviors is a complex task. This is challenging since it requires the identif…