behaviour-policies

Epsilon Greedy Exploration

Reinforcement learning is an artificial intelligence (AI) technique where an agent learns to take actions in an environment to maximize a reward signal. One of the challenges in reinforcement learning is exploring the environment to find the best actions to take while also exploiting the knowledge the agent already has. This is called the exploration-exploitation tradeoff. Too much exploration and the agent might not find the best actions to take. Too much exploitation and the agent might get st

Go-Explore

Go-Explore: Effective Exploration in Reinforcement Learning Reinforcement learning is a technique used in artificial intelligence where an agent learns to take actions in an environment to maximize a reward signal. However, one of the main challenges in reinforcement learning is effective exploration. This is where Go-Explore comes in. Go-Explore is a family of algorithms that aims to solve two common problems with exploration in reinforcement learning: Problem #1: Detachment In reinforceme

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