Reinforcement Learning
ml-agents
TensorBoard
ONNX
Pyramids
deep-reinforcement-learning
ML-Agents-Pyramids
Instructions to use AnnaMats/ppo-Pyramids-Training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use AnnaMats/ppo-Pyramids-Training with ml-agents:
mlagents-load-from-hf --repo-id="AnnaMats/ppo-Pyramids-Training" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
| using NUnit.Framework; | |
| using UnityEngine; | |
| using UnityEditor; | |
| using Unity.MLAgents.Policies; | |
| namespace Unity.MLAgents.Tests | |
| { | |
| [] | |
| public class TestSerialization | |
| { | |
| const string k_oldPrefabPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/old_serialized_agent.prefab"; | |
| const int k_numVecObs = 212; | |
| const int k_numContinuousActions = 39; | |
| [] | |
| public void TestDeserialization() | |
| { | |
| var prefab = AssetDatabase.LoadAssetAtPath<GameObject>(k_oldPrefabPath); | |
| var agent = GameObject.Instantiate(prefab); | |
| var bp = agent.GetComponent<BehaviorParameters>(); | |
| Assert.AreEqual(bp.BrainParameters.ActionSpec.NumContinuousActions, k_numContinuousActions); | |
| Assert.AreEqual(bp.BrainParameters.VectorObservationSize, k_numVecObs); | |
| } | |
| } | |
| } | |