Oct 29, 2024 , Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions
Oct 15, 2024 , Lin (1992) Long-Ji Lin. Self-improving reactive agents based on reinforcement learning, planning and teaching. Machine learning, 8:293–321, 1992.
Oct 16, 2024 , Self-improving reactive agents based on reinforcement learning, planning and teaching. Mach. Learn., 8:293–321, 1992. [23] Rui Liu, Tianyi Wu ...
Oct 15, 2024 , Leveraging the Gym-DSSAT simulation environment, our research enables RL agents to learn optimal fertilization strategies based on variable weather conditions.
Nov 3, 2024 , Learn. Res. 2005, 6, 503–2556. [Google Scholar]; Lin, J. Self improving reactive agents based on reinforcement learning, planning and teaching. J. Mach. Learn.
1 day ago , [22] L.-J. Lin, 'Self-improving reactive agents based on reinforcement learn- ing, planning and teaching', Mach. Learn., ...
Nov 1, 2024 , We show that our deliberative agent achieves greater than 70% improvement over reactive baselines on the challenging TEACh benchmark. ... learning-based agents ...
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Oct 23, 2024 , AI agents are autonomous entities that perceive, process, and act towards specific goals, varying from simple reactive systems to complex self-learning entities ...
Oct 22, 2024 , Reinforcement learning offers to robotics a framework and set of tools for the design of sophisticated and hard-to-engineer behaviors.
Oct 25, 2024 , ER is especially suitable for reinforcement learning teaching because the algorithms behind this approach are designed to operate in systems based on agents, ...
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