Practical Simulations for Machine Learning

Index

A

• actions of agents, Under the Hood and Beyond
  • for CL (curriculum learning), Actions-Actions
  • creating, Letting the Agent Take Actions in the Environment-Letting the Agent Take Actions in the Environment, What’s It All Mean?-What’s It All Mean?
  • discrete versus continuous, Actions
  • in GridWorld environment, Experimenting with an Environment
  • modifying, Modifying the Agent’s Actions-Modifying the Agent’s Actions
• agents
  • adding memory, Building in Unity
  • camera-only, Building a Camera-Only Agent-Seeing What the Agent’s Camera Sees
    • adding cameras to, Adding a New Camera for the Agent-Adding a New Camera for the Agent
    • coding, Coding the Camera-Only Agent-Coding the Camera-Only Agent
    • sensory input needed, Cameras and You
    • training, Training the Camera-Based Agent-Training the Camera-Based Agent
    • view from, Seeing What the Agent’s Camera Sees-Seeing What the Agent’s Camera Sees
  • configuring
    • cooperative learning project, Finalizing the Environment and Agents-Finalizing the Environment and Agents
    • GridWorld environment, Python All the Way Down-Experimenting with an Environment
  • creating
    • block pusher project, The Agent-The Agent, The Environment-The Environment
    • coin collecting project, The Name’s Ball, Agent Ball-The Name’s Ball, Agent Ball
    • cooperative learning project, The agents-The agents
    • curriculum learning project, The Agent-The Agent
    • rolling ball project, The Agent-The Agent
    • self-driving car project, Setting Up for ML-Setting Up for ML
  • definition of, Introducing Synthesis and Simulation
  • initializing, The Agent