Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
For a minimal example of how to use the environment framework, refer to examples/simple-calculator. For the environment and training data used in our paper, see AgentBench FC. For reproducing the ...
anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...
Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
A new computational model of the brain based closely on its biology and physiology not only learned a simple visual category learning task exactly as well as lab animals, but even enabled the ...
A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...
What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.
Abstract: Multi-task multi-agent reinforcement learning (MT-MARL) is capable of leveraging useful knowledge across multiple related tasks to improve performance on any single task. While recent ...
Abstract: This paper addresses the dynamic task assignment problem for multiple uncrewed aerial vehicles (UAVs) operating under weak communication. Existing learning-based methods face two primary ...
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