Christian11
Member
Reinforcement learning (RL) is a machine learning technique where an AI agent learns by interacting with an environment and receiving rewards or penalties for its actions. The goal is to maximize cumulative rewards over time.
For example, an RL-based AI playing chess improves by learning which moves lead to victory. RL is widely used in robotics, gaming, and recommendation systems. Popular frameworks include OpenAI Gym and Deep Q-Networks (DQN).
SOURCE: https://www.inoru.com/ai-agent-development-company
For example, an RL-based AI playing chess improves by learning which moves lead to victory. RL is widely used in robotics, gaming, and recommendation systems. Popular frameworks include OpenAI Gym and Deep Q-Networks (DQN).
SOURCE: https://www.inoru.com/ai-agent-development-company