Hybrid DDQN + A* agent for autonomous search and rescue in partially observable environments.
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Updated
Dec 20, 2025 - Python
Hybrid DDQN + A* agent for autonomous search and rescue in partially observable environments.
Vision-based autonomous racing system comparing PPO, DQN, and GAIL with custom reward shaping across CarRacing-v3 and TORCS simulators
A Master Project implementing a Deep Reinforcement Learning (DDPG) agent for transaction-cost-aware option hedging. Features Behavioral Cloning for a "warm start" and is backtested on real-world SPY ETF data.
Standalone Gym-style wrapper for CityFlow traffic signal control.
An observability-first reinforcement-learning training & benchmarking library, built on PyTorch and Gymnasium.
A reinforcement learning project that trains DQN and PPO agents to trade SPY using technical indicators and portfolio data. Built with Python, Gymnasium, Stable-Baselines3, PyTorch, yfinance, pandas, and scikit-learn, it compares the agents against traditional trading strategies and evaluates them using financial performance metrics.
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