Step 1: TheoryResearch Paper
Playing Atari with Deep Reinforcement Learning
Study the core concepts and background material for this learning item.
Step 2: PracticeKaggle Workbook
Deep Reinforcement Learning Exercise
Solve the challenges and apply your knowledge interactively.
Hard30 min estimated study
Overview
Construct deep reinforcement learning agents using Q-Network architectures.
Learning Objectives
- Formulate policy rewards
- Train Q-network parameters
Prerequisites
Item #88N-Step Lookahead (Minimax)
LockedTracking Control
Completion Reward+300 XP
Study Checklist
Studied theory resource
Completed practice exercise