Artificial Intelligence, or AI, is transforming the way we interact with technology. At the heart of this technology are agents, software programs that can interact with the world and make decisions on our behalf. In this video, we'll explore the different types of agents in AI. The first type of agent is the simple reflex agent. This agent reacts to its environment based on a set of predefined rules. For example, a thermostat that turns on the heat when the temperature drops below a certain level is a simple reflex agent. While these agents can be useful for simple tasks, they have limited abilities and can't handle complex situations. The model-based reflex agent is an improvement on the simple reflex agent. It maintains an internal model of the environment and uses that to make decisions. For example, a robot that navigates a maze by creating a map of the maze and using that to plan its route as a model-based reflex agent. These agents are more flexible and simple reflex agents, but they can still struggle with complex environments. The goal-based agent is designed to achieve a specific goal. It uses a set of rules to determine the best course of action to take to achieve that goal. For example, a chess playing program that aims to win the game as a goal-based agent. These agents are more intelligent than reflex agents, but they can still struggle with uncertain environments. The utility-based agent is similar to the goal-based agent, but it takes into account not only the goal but also the cost of achieving that goal. It uses a utility function to determine the best course of action to take. For example, a self-driving car that aims to get to its destination quickly and safely is a utility-based agent. These agents are more sophisticated than goal-based agents and can handle complex and uncertain environments. Finally, the learning agent is designed to learn from experience. It uses a set of algorithms to analyze its environment and adjust its behavior based on that analysis. For example, a spam filter that learns to recognize new types of spam emails is a learning agent. These agents are the most sophisticated of all and can handle complex and uncertain environments with ease. Each type of agent has its own strengths and weaknesses, but all are important tools in the field of artificial intelligence. As this field continues to evolve, we can expect to see even more advanced types of agents that can handle even more complex tasks. Thanks for reading.