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navground_learning 0.1.0 documentation

Contents:

  • Introduction
  • Installation
  • Tutorials
    • Basics
      • Gymnasium Environment
      • Navground-PettingZoo integration
      • Using a ML policy in Navground
    • Empty environment
    • Corridor with obstacle
      • Scenario
      • Learning
    • Crossing
      • Training one agent among many agents
      • Performance of policies trained in single-agent environment
      • Training agents among peers
      • Performance of policies trained in multi-agent environment
    • Periodic Crossing
      • Uniform speeds
      • Different speeds
  • Guides
    • How to extend
  • Reference
    • Types
    • Indices
    • Configuration
    • Rewards functions
    • Single-agent Gymnasium Environment
    • Multi-agent Pettingzoo Environment
    • Policies
    • Imitation Learning
    • Evaluation
    • Saving and Loading
    • Onnx
    • Navground Components
    • Examples

Python Module Index

n
 
n
- navground
    navground.learning
    navground.learning.behaviors
    navground.learning.config
    navground.learning.env
    navground.learning.evaluation
    navground.learning.examples
    navground.learning.examples.corridor_with_obstacle
    navground.learning.examples.cross
    navground.learning.il
    navground.learning.indices
    navground.learning.io
    navground.learning.onnx
    navground.learning.parallel_env
    navground.learning.policies
    navground.learning.probes
    navground.learning.scenarios
    navground.learning.types

By Jerome Guzzi et al. (IDSIA, USI-SUPSI)

© Copyright 2024, Jerome Guzzi et al. (IDSIA, USI-SUPSI).