Faulty reward functions in the wild

OpenAI Blog2016-12-21 16:000 views

Reinforcement learning algorithms can break in surprising, counterintuitive ways. In this post we’ll explore one failure mode, which is where you misspecify your reward function.

Source：https://openai.com/index/faulty-reward-functions

My favorites

PreviousPixelCNN++: Improving the PixelCNN with discretized logistic mixture likelihood and other modifications NextUniverse

Why clean UI/UX matters when playtesting modded game launchers

When testing multiple game builds and modpack setups, small UI details make a huge difference. Recently, while testing w

0dev.to Testing

How to read a peptide certificate of analysis, section by section

Most certificates of analysis for research peptides get a two second look. Here is what each part actually tells you, in

0dev.to Testing

Failed jobs in Node.js: dead-letter handling with BullMQ

Part 7 of 10: Reliable background jobs in Node.js, from zero . By Sandro Dezerio , senior full-stack engineer. The sign-

0dev.to TypeScript

Reading a golf swing from a 9-axis IMU on a TV box: the calibration notes that actually mattered

A small sensor strapped near the shaft, a TV box rendering the shot, and a player who expects the ball to go where they

0dev.to JavaScript

Build composable, interoperable multi-agent systems with A2A on AWS

Agents in multi-agent systems that span organizational boundaries often need to collaborate in a composable, interoperab

0AWS Machine Learning Blog

Run agents securely and efficiently with the next generation AgentCore runtime

AI agents have moved past one-off prompts. They now run multi-step workloads for hours at a time. The length of task tha