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2025 AAAI AAAI 2025

Towards Robust, Efficient, and Practical Decision-Making: From Reward-Maximizing Deep Reinforcement Learning to Reward-Matching GFlowNets

Abstract

Abstract In this talk, I will present our recent advances in sequential decision-making systems in reward-maximizing deep RL and the emerging reward-matching GFlowNets. The presentation will examine three fundamental challenges: efficiency, robustness, and practical applications.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning and Reinforcement Learning
🧭 Keyword Pioneer — reward matching
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Ling Pan

Topics

Artificial Intelligence > Core AI > Agent Systems Machine Learning > Core Methods > Representation Learning Reinforcement Learning > Methods > Deep RL Reinforcement Learning > Applications > Value Iteration Machine Learning > Learning Types > Reinforcement Learning

Keywords

deep reinforcement learning sequential decision-making reward maximization generative flow network reward matching
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