all AI news
Beyond Value: CHECKLIST for Testing Inferences in Planning-Based RL. (arXiv:2206.02039v1 [cs.AI])
June 7, 2022, 1:10 a.m. | Kin-Ho Lam, Delyar Tabatabai, Jed Irvine, Donald Bertucci, Anita Ruangrotsakun, Minsuk Kahng, Alan Fern
cs.LG updates on arXiv.org arxiv.org
Reinforcement learning (RL) agents are commonly evaluated via their expected
value over a distribution of test scenarios. Unfortunately, this evaluation
approach provides limited evidence for post-deployment generalization beyond
the test distribution. In this paper, we address this limitation by extending
the recent CheckList testing methodology from natural language processing to
planning-based RL. Specifically, we consider testing RL agents that make
decisions via online tree search using a learned transition model and value
function. The key idea is to improve the …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US
Research Engineer
@ Allora Labs | Remote
Ecosystem Manager
@ Allora Labs | Remote
Founding AI Engineer, Agents
@ Occam AI | New York
AI Engineer Intern, Agents
@ Occam AI | US