FIT3080 Notes
About 393 wordsAbout 5 min
MonashCS
2025-08-03
Introduction
Welcome to my study notes for FIT3080 - Artificial Intelligence. This unit delves into the foundational principles of AI, exploring how to design and build intelligent agents that can perceive their environment, reason about their knowledge, and act to achieve goals.
From classic search algorithms to modern machine learning concepts, this course provides a comprehensive overview of the field. These notes are my attempt to structure and document my learning journey through this fascinating subject.
What You'll Find Here
Core Topics Covered:
- Foundations of AI: The history, philosophy, and future of Artificial Intelligence.
- Intelligent Agents: Exploring different types of agents (simple reflex, model-based, goal-based, utility-based) and their environments.
- Problem-Solving with Search:
- Uninformed search strategies (BFS, DFS, IDS).
- Informed (Heuristic) search strategies (Greedy Best-First, A*).
- Local search and optimization problems.
- Adversarial Search: Techniques for game-playing agents (Minimax, Alpha-Beta Pruning).
- Knowledge, Reasoning, and Planning: How agents can represent knowledge and make logical deductions.
- Uncertainty: Handling incomplete or uncertain information with probability.
- Machine Learning: An introduction to how agents can learn from experience.
Current Content
📚 AI Basics: Core concepts and an introduction to the field.
📚 Intelligent Agents: Detailed exploration of agent architectures and their design principles.
📚 Search: In-depth coverage of various search algorithms for problem-solving.
More sections will be added as the unit progresses, including topics like logic, planning, and machine learning.
Skills You'll Develop
- Algorithmic Thinking: Designing and implementing complex search algorithms.
- Problem Decomposition: Breaking down complex problems into manageable sub-problems suitable for AI techniques.
- Logical Reasoning: Understanding how to represent knowledge and perform automated reasoning.
- Critical Analysis: Evaluating the trade-offs between different AI algorithms and approaches.
Applications & Real-World Impact
Artificial Intelligence is transforming industries worldwide:
- Gaming: Creating intelligent and challenging non-player characters (NPCs).
- Robotics: Enabling robots to navigate, plan, and interact with the physical world.
- Logistics & Planning: Optimizing supply chains and scheduling complex operations.
- Natural Language Processing (NLP): Powering virtual assistants, translation services, and sentiment analysis.
- Autonomous Vehicles: The brains behind self-driving cars.
- Medical Diagnosis: Assisting doctors in identifying diseases from medical imaging and data.
These notes are intended to be a living document of my learning process. Let's explore the exciting world of AI together! 🚀
Changelog
1f4fb-feat: drop section for AI basicon
Copyright
Copyright Ownership:WARREN Y.F. LONG
License under:Attribution-NonCommercial-NoDerivatives 4.0 International (CC-BY-NC-ND-4.0)