• 1.An intelligent agent is a computational entity that perceives its environment through sensors and takes actions to achieve specific goals or objectives. It can be a software program, a robot, or any system capable of making decisions.
• 2.Intelligent agents are designed to exhibit autonomous behavior, meaning they can operate independently and make decisions without human intervention.
• 3.They are equipped with some form of artificial intelligence or decision-making capabilities, which allow them to analyze their environment and take actions accordingly.

Formal Definitions for Artificial Intelligence

Systems that think like humans Systems that act like humans “The exciting new effort to make computers think … machines with minds, in the full and literal sense” (Haugeland, 1985) “The art of creating machines that perform functions that require intelligence when performed by people” (Kurzweil 1990) “[The automation of] activities that we associate with human thinking, activities such “The study of how to make computers do things at which, at the moment, people are as decision making, problem solving, learning …” (Bellman, 1978).

Components of Intelligent Agents:

1. 1.Sensors: These are the perceptual mechanisms that allow the agent to gather information from its environment. Sensors can include cameras, microphones, temperature sensors, and more.
2. Actuators: Actuators are responsible for executing the actions or commands generated by the agent. Examples include motors, speakers, and other output devices
3. Agent Program: This is the software or logic that processes the sensor inputs and determines the actions to take. It's the "intelligence" of the agent.

Types of Environments

1.Fully Observable vs. Partially Observable: An environment is fully observable if the agent's sensors provide complete information about its state. If the agent has limited or incomplete information, the environment is partially observable.

2.Deterministic vs. Stochastic: In a deterministic environment, the outcomes of actions are predictable. In a stochastic environment, there is an element of randomness or uncertainty.

3.Static vs. Dynamic: A static environment remains unchanged while the agent operates, while a dynamic environment can change over time.

4.Discrete vs. Continuous: An environment may have discrete states and actions, or it may involve continuous variables.