He also discussed the "education" of such machines "by means of rewards and punishments." Turing's ideas ultimately led to the development of reinforcement learning, a branch of artificial ...

Figure 02's human-like gait is the product of the company's simulated reinforcement learning system, and is just the beginning of its plans to make its robots perform physical tasks more naturally.

Rule-based reinforcement learning (RL) or reinforcement fine-tuning (RFT) is a promising alternative, requiring only dozens to thousands of samples instead of massive datasets. Various approaches have ...

Abstract: This paper proposes a deep reinforcement learning scheme for the primary frequency response of floating offshore wind turbines (FOWTs). Considering the fact that current FOWT simulators ...

Separately, Databricks said it has found a new fine-tuning method that leverages Test-time Adaptive Optimization, a type of reinforcement learning that make it easier to build agents for a ...

So they started building reasoning systems. Last year, companies like OpenAI began to lean heavily on a technique called reinforcement learning. Through this process — which can extend over ...

Moreover, conventional reinforcement learning methods require expensive reward models that may not fully capture the nuanced and subjective nature of human feedback. A team of researchers from China ...

Then, by comparing the fluidity, flexural strength, and compressive strength of fiber basic magnesium sulfate cement and through the comparison of microstructures of BF and CF in the BMSC mortar, the ...

Abstract: The flexural ultrasonic transducer (FUT) is a sensor primarily composed of a circular metallic plate, to which a piezoelectric ceramic disc is bonded. The vibrations generated from the ...