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cs.LG2025
Interactive Groupwise Comparison for Reinforcement Learning from Human Feedback
Jan Kompatscher, Danqing Shi, Giovanna Varni +2
Reinforcement learning from human feedback (RLHF) has emerged as a key enabling technology for aligning AI behaviour with human preferences. The traditional way to collect data in…
cs.LG2024
AgentForge: A Flexible Low-Code Platform for Reinforcement Learning Agent Design
Francisco Erivaldo Fernandes Junior, Antti Oulasvirta
Developing a reinforcement learning (RL) agent often involves identifying values for numerous parameters, covering the policy, reward function, environment, and agent-internal arch…