Скачать или смотреть Chapter 1–Building basic UI Gym for Reward Engineering | Create Basic E-commerce Purchase AI Agent

What’s Coming Next
Chapter 2: Tic-Tac-Toe — state, turns, adversaries
Chapter 3: Browser agents — Playwright + Python
Chapter 4: E-Commerce purchase ai assistants — GPUs, cost, and reality (in A100 GPUS)

Everyone talks about: Bigger models, More GPUs, Better RL algorithms

But in real systems, the most expensive and valuable part of reinforcement learning is reward engineering.

This video explains why reward engineering is becoming a serious business, and how to understand it using the simplest possible Gym environment.

hapter 1: The Linear World (What We Build)

We build a tiny Gym environment:

A dot moves on a line from 0 → 10

Two actions: left or right

One reward: reach the goal

This environment lets us explain:

Why reward timing matters

Why sparse rewards are dangerous

Why agents can “technically succeed” but still behave badly

#RewardEngineering
#ReinforcementLearning
#AIAgents
#AIEngineering
#MachineLearning
#AgenticAI
#Gymnasium
#NoGPU
#AIProduct