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métricas de evaluación de rendimiento

  • Open-source Python framework implementing multi-agent reinforcement learning algorithms for cooperative and competitive environments.
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    What is MultiAgent-ReinforcementLearning?
    This repository provides a complete suite of multi-agent reinforcement learning algorithms—including MADDPG, DDPG, PPO, and more—integrated with standard benchmarks like the Multi-Agent Particle Environment and OpenAI Gym. It features customizable environment wrappers, configurable training scripts, real-time logging, and performance evaluation metrics. Users can easily extend algorithms, adapt to custom tasks, and compare policies across cooperative and adversarial settings with minimal setup.
    MultiAgent-ReinforcementLearning Core Features
    • Implementations of MADDPG, DDPG, PPO
    • Environment wrappers for Multi-Agent Particle and Gym
    • Configurable training and evaluation scripts
    • Real-time logging with TensorBoard
    • Modular codebase for extension
  • Simulate technical coding interviews with ChatGPT, generating questions and providing real-time code evaluation and feedback.
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    What is AI Interview Prep?
    AI Interview Prep enables developers to practice technical interviews in a realistic, interactive environment. It uses ChatGPT to create coding challenges on demand, then compiles and runs your solutions, comparing outputs against expected results. The tool provides detailed feedback, suggestions for improvement, and performance metrics to help you identify strengths and weaknesses. You can select topics, languages, and difficulty levels, and review session history to monitor progress.
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