CS311: Artificial Intelligence – Middlebury College

Overview

This repository contains coursework and project implementations from CS311: Artificial Intelligence, completed at Middlebury College in Spring 2025. The course provided a comprehensive introduction to core AI concepts and algorithms, with a focus on problem-solving, decision-making, and learning. Projects were implemented in Python and covered a range of AI paradigms, from classical search to machine learning.

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🧠 Topics Covered

🔍 Search Algorithms

• Breadth-First Search (BFS)
• A* Search with custom heuristics
• Eight Puzzle Solver with Manhattan and Linear Conflict heuristics

🕹️ Adversarial Agents

• Minimax and Alpha-Beta Pruning
• Depth-limited adversarial search
• Expectimax strategy for stochastic opponents
• Pac-Man AI Agent with tuned evaluation functions

🧩 Constraint Satisfaction Problems (CSP)

• Sudoku Solver using:
  • AC-3 algorithm (Arc Consistency)
  • Backtracking Search
  • Most Constrained Variable and Least Constraining Value heuristics
  • Forward Checking with domain restoration

💬 Natural Language Processing (NLP)

• Naive Bayes Sentiment Classifier
• Text preprocessing, tokenization, and feature extraction
• Evaluation using accuracy and confusion matrix on real-world datasets

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