Herein, we synthesized PCN-222, a zirconium-based porphyrinic metal–organic framework (MOF) with preferential longitudinal growth as a series of particles with ARs increasing from 3.4 to 54. The ...

This paper presents a parameterized batch reinforcement learning algorithm for near-optimal longitudinal control of autonomous land vehicles (ALVs). The proposed approach uses an actor-critic ...

Reinforcement learning has also had an unexpected impact on neuroscience. The neurotransmitter dopamine plays a key role in reward-driven behaviors in humans and animals.

Their book, “Reinforcement Learning: An Introduction,” which was published in 1998, remains the definitive exploration of an idea that many experts say is only beginning to realize its potential.

TL;DR Key Takeaways : Reinforcement fine-tuning (RFT) is a new AI training method by OpenAI that enhances reasoning and adaptability, allowing models to tackle complex, specialized tasks with ...

OpenAI’s Reinforcement Fine-Tuning (RFT) unlocks AI’s potential with data efficiency, performance optimization, and domain-specific reasoning.

Longitudinal and computational analyses reveal an early and temporally stable hippocampal and striatal involvement in reinforcement learning in 6-to-7-year-old children.

This indeed seems to be the case, and we added this point in our discussion in line 639-643: “Adult studies that examined feedback timing during reinforcement learning reported average learning rates ...

Learning from the past is critical for shaping the future, especially when it comes to economic policymaking. Building upon the current methods in the application of Reinforcement Learning (RL) to the ...

Reinforcement learning techniques could be the keys to integrating robots — who use machine learning to output more than words — into the real world.