Proximal Policy Optimization (Ppo)
A reinforcement learning algorithm that aims to maximize the expected reward of an agent interacting with an environment, while minimizing the divergence between the new and old policy.
Areas of application
- Robotics
- Reinforcement learning
- Autonomous vehicles
- Traffic scenarios
- Rough terrain
Example
PPO is commonly used in robotics to train autonomous vehicles to navigate through complex environments, such as traffic scenarios or rough terrain. By minimizing the divergence between the new and old policy, PPO can help ensure that the vehicle’s behavior remains predictable and controllable over time.