A1 - Example Pool

• MLPro-BF - Basic Functions
  • Layer 0 - Elementary Functions
    • Various Functions
      • Howto BF-001: Logging
      • Howto BF-002: Timer
      • Howto BF-003: Store and plot data
      • Howto BF-004: Buffers
      • Howto BF-005: Persistence
    • User Interaction
      • Howto BF-UI-001: SciUI - Reuse of interactive 2D/3D Input Space
  • Layer 1 - Computation
    • Event Handling
      • Howto BF-EH-001: Event Handling
    • Multitasking
      • Howto BF-MT-001: Multitasking - Parallel Algorithms
      • Howto BF-MT-002: Multitasking - Tasks and Workflows
  • Layer 2 - Mathematics
    • Howto BF-MATH-001: Dimensions, Spaces and Elements
    • Howto BF-MATH-010: Normalizers
  • Layer 3 - Application Support
    • Stream Processing
      • Howto BF-STREAMS-001: Accessing Native Data From MLPro
      • Howto BF-STREAMS-002: Accessing Data From CSV Files
      • Howto BF-STREAMS-003: Visualizing 10-dimensional Random Stream Provided By MLPro
      • Howto BF-STREAMS-004: Visualizing 2D Double Spiral Stream Provided By MLPro
      • Howto BF-STREAMS-005: Visualizing Multivariate Point Outlier Stream Provided By MLPro
      • Howto BF-STREAMS-006: Visualizing Static 2D Random Point Clouds Provided By MLPro
      • Howto BF-STREAMS-007: Visualizing Dynamic 2D Random Point Clouds Provided By MLPro
      • Howto BF-STREAMS-008: Visualizing Static 3D Random Point Clouds Provided By MLPro
      • Howto BF-STREAMS-009: Visualizing Dynamic 3D Random Point Clouds Provided By MLPro
      • Howto BF-STREAMS-010: Visualizing Multivariate Random Cloud Generator in 3D Mode Provided By MLPro
      • Howto BF-STREAMS-020: Streams Sampler
      • Howto BF-STREAMS-101: Basics of Streams
      • Howto BF-STREAMS-102: Tasks Workflows And Stream Scenarios
      • Howto BF-STREAMS-110: Window
      • Howto BF-STREAMS-111: Rearranger (2D)
      • Howto BF-STREAMS-112: Rearranger (3D)
      • Howto BF-STREAMS-113: Rearranger (nD)
      • Howto BF-STREAMS-114: Deriver
    • Physics
      • Howto BF-PHYSICS-001: Transfer Functions
      • Howto BF-PHYSICS-002: Unit Converter
    • State-based Systems
      • Howto BF-SYSTEMS-001: Demonstrating Native Systems
      • Howto BF-SYSTEMS-010: System, Controller, Actuator, Sensor
      • Howto BF-SYSTEMS-011: Double Pendulum Systems wrapped with MuJoCo
      • Howto BF-SYSTEMS-012: Cartpole Continuous Systems wrapped with MuJoCo
      • Howto BF-SYSTEMS-013: MuJoCo Simulation with Camera
  • Layer 4 - Machine Learning
    • Basics
      • Howto BF-ML-001: Adaptive Model
      • Howto BF-ML-010: Hyperparameters
    • Adaptive State-based Systems
• MLPro-SL - Supervised Learning
• MLPro-RL - Reinforcement Learning
  • Elementary or Uncategorized Topics
    • Howto RL-001: Reward
  • Environments
    • Howto RL-ENV-003: Run Agent with random Policy in Double Pendulum MuJoCo Environment
  • Adaptive Environments
    • Howto RL-AE-001: Available Soon
  • Model-based Reinforcement Learning
    • Howto RL-MB-001: Train a model-based Agent on native Grid World Environment
  • 3rd Party Support
• MLPro-GT - Game Theory
  • Dynamic Games
    • Howto GT-DG-001: Run Multi-Player with Own Policy
    • Howto GT-DG-002: Train Multi-Player
    • Howto GT-DG-003: Train Multi-Player in Potential Games
    • Howto GT-DG-004: Train Multi-Player in Stackelberg Games
  • Native GT
    • Howto GT-Native-001: 2P Prisoners’ Dilemma
    • Howto GT-Native-002: 3P Prisoners’ Dilemma
    • Howto GT-Native-003: Rock, Paper, Scissors
    • Howto GT-Native-004: 3P Supply and Demand
    • Howto GT-Native-005: 3P Routing Problems
• MLPro-OA - Online Adaptivity