JC AI research lab
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- Poland
- cyranka@mimuw.edu.pl
Popular repositories Loading
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Unified-Long-Horizon-Time-Series-Benchmark
Unified-Long-Horizon-Time-Series-Benchmark PublicCode for reproducing results from the paper "Unified Long Horizon Time Series Benchmark"
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unity-ml-agents_hide-and-seek
unity-ml-agents_hide-and-seek PublicNew Unity ML-Agents Team-based MARL environments: Hide & Seek and Predator-Prey. Used in the paper "FCSP: Fictitious Co-Self-Play for Team-based Multi-agent Reinforcement Learning"
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ml-agents_fork
ml-agents_fork PublicForked from Unity-Technologies/ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement …
C#
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unity_dodgeball_training_fork
unity_dodgeball_training_fork Public archiveForked from Unity-Technologies/ml-agents-dodgeball-env
Repository with environment C# code for training GFCP algorithm (team self-play with checkpoint injections) using ML-Agents learn script
C#
Repositories
- FreTS-fork Public Forked from aikunyi/FreTS
Official implementation of the paper "Frequency-domain MLPs are More Effective Learners in Time Series Forecasting"
- unity-ml-agents_hide-and-seek Public
New Unity ML-Agents Team-based MARL environments: Hide & Seek and Predator-Prey. Used in the paper "FCSP: Fictitious Co-Self-Play for Team-based Multi-agent Reinforcement Learning"
- marl_team_based_testers Public
Python scripts dedicated for testing team-based multi-agent reinforcement learning environments. Behavioral policies of agents are provided as ONNX checkpoints. Currently compatible with Unity ML-Agents framework.
- Unified-Long-Horizon-Time-Series-Benchmark Public
Code for reproducing results from the paper "Unified Long Horizon Time Series Benchmark"
- worrisome-nn Public
Code repository for reproducing results published in ECAI23 paper entitled "Worrisome Properties of Neural Network Controllers and Their Symbolic Representations"
- unity_dodgeball_training_fork Public archive Forked from Unity-Technologies/ml-agents-dodgeball-env
Repository with environment C# code for training GFCP algorithm (team self-play with checkpoint injections) using ML-Agents learn script
- improved_overparametrization_tmlr Public
Code for reproducing experiments reported in the TMLR paper 'Improved Overparametrization Bounds for Global Convergence of Stochastic Gradient Descent for Shallow Neural Networks'
- ml-agents_fork Public Forked from Unity-Technologies/ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
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