Deep reinforcement learning (DRL) algorithms have become a key intersection of deep ... (DQN), trust region policy optimization (TRPO), proximal policy optimization (PPO), and others, outlining their ...

We propose a proximal policy optimization with graph transformer (GT-PPO) algorithm, which leverages proximal policy optimization (PPO) as the foundational framework, to address this problem for the ...

Building on this, our work focuses on using PPO algorithm and improving it by optimizing hyperparameters ... Tumer, "Evolution-Guided Policy Gradient in Reinforcement Learning," in Proc. AAAI ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like ...

This is a potentially valuable modeling study on sequence generation in the hippocampus in a variety of behavioral contexts. While the scope of the model is ambitious, its presentation is incomplete ...

In addition, reinforcement learning algorithm has been applied for the control of the three section continuum robot. Since the robot control problem is continuous, traditional algorithms of ...