Intro to Artificial Intelligence - Heuristic Search and the A* Algorithm - Lecture 5
Explore heuristic search techniques and the A* algorithm for efficient problem-solving in AI, with practical applications in game development.
Introduction to Artificial Intelligence: A* Search Algorithm and Optimizations - Lecture 6
Explore A* search algorithm implementation, heuristic functions, and optimization techniques for pathfinding in grid-based environments with varying object sizes and connectivity constraints.
Introduction to Artificial Intelligence - Assignment 1 Overview - Lecture 4
Explore AI fundamentals through grid world environments, implementing BFS and DFS algorithms. Learn code structure, GUI development, and key functions for search algorithms in game-like scenarios.
Introduction to Artificial Intelligence - Problem Solving and Search - Lecture 3
Explore problem-solving techniques and search algorithms in AI, applying learned concepts to simple games for practical understanding.
Introduction to Artificial Intelligence - Hash Functions and Tables - Lecture 7
Explore hash functions and tables in AI, learning algorithmic techniques for efficient data storage and retrieval in modern problem-solving environments.
Introduction to Artificial Intelligence - Game Theory Part 1 - Lecture 8
Explore game theory fundamentals and its applications in AI, focusing on strategic decision-making and problem-solving techniques in competitive environments.
Intro to Artificial Intelligence - Minimax and AlphaBeta Search - Lecture 10
Explore Minimax and AlphaBeta Search algorithms for game AI, learning key techniques to optimize decision-making in adversarial environments.
Game Programming: Sprites, Textures, and Animations - Lecture 9
Explore sprite rendering, texture management, and animation techniques for game development using C++ and SFML graphics library.
Introduction to Artificial Intelligence - Evolutionary Computing - Lecture 12
Explore evolutionary computing techniques for AI problem-solving, including genetic algorithms and their applications in optimization and game AI.
Introduction to Artificial Intelligence - Reinforcement Learning - Lecture 14
Explore reinforcement learning fundamentals in AI, covering key concepts and techniques for problem-solving in modern environments.
Pathfinding and Steering in Game Programming - Lecture 15
Explore pathfinding and steering techniques in game development, enhancing AI movement and navigation for more realistic and engaging gameplay.
Introduction to Artificial Intelligence - Bandit Algorithms - Lecture 15
Explore bandit algorithms in AI, learning key concepts and applications for modern problem-solving in gaming environments.
Intro to Artificial Intelligence - Temporal Difference Learning - Lecture 18
Explore temporal difference learning and its applications in AI, with practical insights for Assignment 5 implementation.
C++ Visual Code Profiling for Game Programming - Lecture 20
Learn C++ Visual Code profiling techniques for game programming, focusing on performance optimization and efficient code analysis.
Game Programming: Introduction to Shaders - Lecture 21
Explore game shader fundamentals, including rendering techniques, animation, and graphics programming for enhanced visual effects in game development.
Introduction to Artificial Intelligence: Neural Networks - Lecture 19
Explore fundamental concepts of neural networks in AI, including structure, functionality, and applications in modern problem-solving environments.
Intro to Artificial Intelligence - Deep Neural Networks - Lecture 20
Explore deep neural networks, their architecture, and applications in AI. Learn key concepts and techniques for implementing advanced machine learning models.
Introduction to Artificial Intelligence - Agents and Environments - Lecture 2
Explore AI agents and environments, learning key concepts and techniques for modern problem-solving in artificial intelligence.
Introduction to Artificial Intelligence - Lecture 1: Course Introduction and What is AI?
Explore fundamental AI concepts, including the Turing Test and Chinese Room Analogy. Learn about AI applications in games and its capabilities. Gain insights into academic integrity and course expectations.
Introduction to Artificial Intelligence - Agents and Environments - Lecture 2
Explore AI agents and environments, learning key concepts and structures for modern problem-solving in intelligent systems.
Problem Solving and Search in Artificial Intelligence - Lecture 3
Explore problem-solving agents, search algorithms, and graph theory in AI. Learn about BFS, DFS, UCS, and more. Gain practical insights for implementing efficient search strategies.