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1. Multi-Agent-Implementation-In-Context-of-PacMan Multi-Agent-Implementation-In-Context-of-PacMan Public

   Project 2: Multi-Agent Pacman - Introduces multiple agents (ghosts) and competition. Built intelligent agents for both Pacman and the ghosts using techniques like minimax search and design evaluati…

   Python

2. Search-Algorithms-in-Context-Of-Pacman Search-Algorithms-in-Context-Of-Pacman Public

   Focuses on implementing search algorithms (DFS, BFS, UCS, A*) to help Pacman navigate mazes efficiently, finding specific locations and collecting food.

   Python

3. Probabilistic-Reasoning-in-context-of-Pacman Probabilistic-Reasoning-in-context-of-Pacman Public

   Built Pacman agents with sensors to locate and capture invisible ghosts using concepts like Bayesian networks and hidden Markov models. This project emphasizes probabilistic reasoning in a game env…

   Python

4. File-Search-Utility-in-C File-Search-Utility-in-C Public

   I set out to create a simple yet powerful command-line tool designed for efficient file searching and processing. This project is a deep dive into the essential file operations provided by the C p…

   C

5. Mario-Bros-AI-Training Mario-Bros-AI-Training Public

   This project ("MarioBros_Q_Learning.ipynb") uses a Jupyter notebook to train Mario, from the classic game, to play through its environment using Q-learning, a form of reinforcement learning (RL).

   Jupyter Notebook