In various tasks within IsaacLab, PPO, an on-policy reinforcement learning algorithm, is primarily used as the default example algorithm rather than off-policy methods such as SAC or DDPG. This might ...

Abstract: In order to solve the problems of slow convergence speed of the traditional deep reinforcement learning proximal strategy optimization (PPO) algorithm, an RPPO algorithm for continuous robot ...

The hockey environment is a game between two players (player1 and player2). We can control the left player (player1) The task is to maximize the cumulative reward (=sum of rewards over all timesteps).

Abstract: Interest in applying Reinforcement Learning (RL) to Autonomous Vehicles (AVs) is experiencing a rapid and substantial expansion. Proximal Policy Optimization (PPO), a well-known RL algorithm ...

In tactical communication networks, highly dynamic topologies and frequent data exchanges create complex spatiotemporal dependencies among link states. However, most existing intelligent routing ...