Introduction and Foundations of AI

• Artificial intelligence (AI) is the study of how to create machines and systems that can perform tasks that normally require human intelligence, such as perception, reasoning, learning, decision making, and natural language processing.
• AI can be classified into two main categories: narrow AI and general AI. Narrow AI refers to systems that can perform specific tasks well, such as face recognition, speech recognition, or chess playing. General AI refers to systems that can exhibit human-like intelligence across a wide range of domains and tasks, such as common sense reasoning, creativity, or social skills. General AI is still a long-term goal of AI research.
• AI can also be classified into two main approaches: symbolic AI and sub symbolic AI. Symbolic AI uses symbols and rules to represent and manipulate knowledge, such as logic, ontologies, and expert systems. Sub symbolic AI uses numerical and statistical methods to learn from data and experience, such as artificial neural networks, evolutionary algorithms, and reinforcement learning.
• AI is an interdisciplinary field that draws from various disciplines, such as computer science, mathematics, psychology, philosophy, linguistics, and neuroscience. AI also has many applications in various domains, such as health care, education, entertainment, security, and business.

AI systems are computer programs that mimic human intelligence to perform tasks like speech recognition, decision-making, and pattern identification. They fall into several categories:

• Machine learning: Systems learn from data and improve performance without explicit programming. It includes supervised learning (learning from labeled data), unsupervised learning (learning from unlabeled data), and reinforcement learning (learning from actions and rewards).
• Deep learning: A subset of machine learning that uses artificial neural networks to process data and perform tasks like image recognition and natural language processing.
• Robotics: Combines machine learning and computer vision to create machines that interact with their environment, performing tasks like navigation and manipulation.
• Expert systems: Uses knowledge representation to provide expert advice for specific domains. They use rules-based methods to encode facts and logic.
• Fuzzy logic: Uses fuzzy sets and rules to handle uncertainty in data, allowing for degrees of truth rather than binary values.
• Natural language processing: Handles systems that understand and generate natural language, including tasks like speech recognition, machine translation, sentiment analysis, and text summarization.

These are some of the main branches of AI systems and their applications. If you want to learn more about them, you can check out these sources: [6 Major Branches of Artificial Intelligence] 1, [The 6 Branches of Artificial Intelligence Explained] 2, What Is Artificial Intelligence? Definition3.

Intelligent Agents

• An intelligent agent is a system that can perceive its environment through sensors and act upon it through actuators.
• An intelligent agent can be rational, meaning it tries to maximize some performance measure based on its percepts and actions.
• An intelligent agent can have different types of architectures, such as reflex-based, goal-based, utility-based, or learning-based.

Agents and Environments

• The properties of an environment influence the design and performance of an agent.

• An agent is anything that interacts with an environment, which is the part of the world that the agent can perceive and affect.

• An environment can have different properties, such as fully observable or partially observable, deterministic or stochastic, episodic or sequential, static or dynamic, discrete or continuous, single-agent or multi-agent, competitive or cooperative, etc.

Sensors and Actuators

• Sensors are the devices that allow an agent to receive information from the environment, such as cameras, microphones, thermometers, etc.
• Actuators are the devices that allow an agent to affect the environment, such as motors, speakers, heaters, etc.

• Sensors and actuators can have different levels of accuracy, reliability, and cost.

The Concept of Rationality