Something extraordinary has happened, even if we haven’t fully realized it yet: algorithms are now capable of solving intellectual tasks. These models are not replicas of human intelligence. Their ...

Abstract: This work compares two modern optimization approaches for analog integrated circuit sizing: evolutionary algorithms (EAs) and reinforcement learning (RL). While EAs have demonstrated ...

As artificial intelligence continues to integrate into various aspects of our lives, the next frontier in AI technology is quickly ...

This study from MIT explores eye evolution through AI simulations, uncovering how different tasks shape visual systems and their neural processing requirements.

Abstract: To solve the computationally heavy inversion of the soil thermal resistivity and the real time ampacity of power cable, a reinforcement learning-based two-modes (Mode 1 and Mode 2) ...

According to God of Prompt on Twitter, DeepMind has published groundbreaking research in Nature led by David Silver, introducing an AI meta-learning system capable of autonomously discovering entirely ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...

W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...

A Comparative Study of Multi-Objective and Neuroevolutionary-based Reinforcement Learning Algorithms for Optimizing Electric Vehicle Charging and Load Management ...