2 papers
cs.LG2026
Using Reward Uncertainty to Induce Diverse Behaviour in Reinforcement Learning
Anthony GX-Chen, Ankit Anand, Gheorghe Comanici +7
Classical reinforcement learning (RL) typically seeks a deterministic policy that maximizes the expected sum of a scalar reward. Yet, modern applications such as language model fin…
cs.AI2025
Cracking the Code of Action: a Generative Approach to Affordances for Reinforcement Learning
Lynn Cherif, Flemming Kondrup, David Venuto +3
Agents that can autonomously navigate the web through a graphical user interface (GUI) using a unified action space (e.g., mouse and keyboard actions) can require very large amount…