---
title: "reinforcement learning"
type: concept
related: [Model Free Reinforcement Learning, Reinforcement Learning, Model Based Reinforcement Learning, Decision Making, Agent]
source: https://www.jemoka.com/posts/kbhreinforcement_learning/
confidence: high
status: active
---

reinforcement learning is a decision making method with no known model of the environment at all.
agent interacts with environment directly designer provide a performance measure of the agent in the environment agent tries to optimize the decision making algorithm to maximise the performance measure Note: agent&rsquo;s own choice of action, in this case, actually influences how the environment works (and what futures the agent sees). So the agent&rsquo;s actions will influence the environment outcomes
contrast v. explicit programming v. planning Note 2: look ma, no model! unlike optimization, reinforcement learning tasks does not require an optimization objective connected to a model of the environment where we know what knobs to turn. Instead, the objective is a literal performance of how the agent is doing in the actual environment.
contents model-based reinforcement learning model-free reinforcement learning
