180: Reinforcement Learning

Programming Throwdown

Intro topic: Grills

News/Links:

• You can’t call yourself a senior until you’ve worked on a legacy project
  • https://www.infobip.com/developers/blog/seniors-working-on-a-legacy-project
• Recraft might be the most powerful AI image platform I’ve ever used — here’s why
  • https://www.tomsguide.com/ai/ai-image-video/recraft-might-be-the-most-powerful-ai-image-platform-ive-ever-used-heres-why
• NASA has a list of 10 rules for software development
  • https://www.cs.otago.ac.nz/cosc345/resources/nasa-10-rules.htm
• AMD Radeon RX 9070 XT performance estimates leaked: 42% to 66% faster than Radeon RX 7900 GRE
  • https://www.tomshardware.com/tech-industry/amd-estimates-of-radeon-rx-9070-xt-performance-leaked-42-percent-66-percent-faster-than-radeon-rx-7900-gre

Book of the Show

• Patrick:
  • The Player of Games (Ian M Banks)
    • https://a.co/d/1ZpUhGl (non-affiliate)
• Jason:
  • Basic Roleplaying Universal Game Engine
    • https://amzn.to/3ES4p5i
      
      

Patreon Plug https://www.patreon.com/programmingthrowdown?ty=h

Tool of the Show

• Patrick:
  • Pokemon Sword and Shield
• Jason:
  • Features and Labels ( https://fal.ai )

Topic: Reinforcement Learning

• Three types of AI
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
• Online vs Offline RL
• Optimization algorithms
  • Value optimization
    • SARSA
    • Q-Learning
  • Policy optimization
    • Policy Gradients
    • Actor-Critic
    • Proximal Policy Optimization
• Value vs Policy Optimization
  • Value optimization is more intuitive (Value loss)
  • Policy optimization is less intuitive at first (policy gradients)
  • Converting values to policies in deep learning is difficult
• Imitation Learning
  • Supervised policy learning
  • Often used to bootstrap reinforcement learning
• Policy Evaluation
  • Propensity scoring versus model-based
• Challenges to training RL model
  • Two optimization loops
    • Collecting feedback vs updating the model
  • Difficult optimization target
    • Policy evaluation
• RLHF & GRPO

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