Linh Bui's Vlog

The Role of Search Algorithms in AI Search algorithms are essential tools in AI, helping solve complex problems, especially in single-agent games like puzzles and pathfinding. These algorithms systematically explore possibilities, seeking the most efficient path to a goal. Single-Agent Pathfinding Problems Examples of single-agent pathfinding problems include: Tile Games (3x3, 4x4, 5x5 puzzles): The player arranges tiles in a grid by moving a blank space. Travelling Salesman Problem (TSP): Finding the shortest path through a series of cities. Rubik’s Cube, Theorem Proving: Solving complex, structured problems by exploring state configurations. Core Terminology in Search Problem Space: The environment where the search happens, comprising states and operators. Problem Instance: Defined by an initial state and a goal state. Problem Space Graph: A visual of states (nodes) and possible moves (edges). Depth of Problem: The shortest path from the initial to the goal state. Space & ...

Exploring the Expansive Research Domains of AI Artificial intelligence spans a vast array of research areas, each making strides in developing technology that can perform human-like tasks. Below, we dive into some of the most prominent and promising research areas within AI. Speech and Voice Recognition Often discussed in the realms of robotics, expert systems, and natural language processing, speech recognition and voice recognition have unique goals and applications, despite sometimes being used interchangeably. Speech Recognition Focuses on comprehending what is being said. It is useful for hands-free computing, navigation, and controlling devices through spoken commands. Importantly, speech recognition typically does not require individual-specific training and can work with various speakers. Voice Recognition Aims to identify who is speaking by analyzing voice characteristics such as tone, pitch, and accent. This system is person-specific and requires training to recognize ind...