An agent is an entity that perceives its environment through sensors and acts upon it using actuators. An environment is the external context in which an agent operates. The document discusses different types of agents including human agents, robotic agents, simple reflex agents, model-based reflex agents, goal-based agents, utility-based agents, and learning agents. It also describes the key components of an agent as perception, decision-making, action, and knowledge base. Finally, it provides an example of a self-driving car as an agent that must safely navigate road environments using sensors and actuators.

1. Agents and
environment

2. Presented By :
Shahzaib Ali Faiz (20-ARID-44)
M.Usman Ashfaq(20-ARID-4407)
Sheikh Irfan(20-ARID-44)

3. Introduction:
• Title: "Agents and Environments"
• Briefly introduce the topic and its significance in artificial
intelligence and robotics.

4. Definitions
Define an agent : An entity that perceives its environment through sensors and
acts upon it using actuators.
Define an environment: The external context in which an agent operates and
interacts.

5. Agents and environmen
• Human agent:
Sensors: eyes , ears , and other organs
Actuators: Hands, legs, mouth and other body parts
Robotic agent:
Sensor: camera and infrared range finder
Actuator: various motors

6. Agent Characteristics
• Autonomous: Agents have control over their actions and operate
independently.
• Goal-driven: Agents have specific objectives or goals they aim to
achieve.
• Reactive: Agents react to the current state of the environment.
• Proactive: Agents take initiatives and plan ahead to achieve their
goals.
• Learning: Agents can acquire knowledge and improve their
performance through learning.

7. Components of an Agent
• Perception/Sensors: Agents receive input from the environment
• through sensors.
• Decision-making: Agents process the received data and make
decisions based on their goals and internal knowledge.
• Action/Actuators: Agents act upon the environment using
actuators to achieve their goals.
• Knowledge base: Agents store and use internal knowledge to
make decisions.

8. Types of Agents
• Simple Reflex Agents: Agents select actions based on the current
percept without considering the history or future consequences.
• Model-Based Reflex Agents: Agents maintain an internal model of the
world and use it to make decisions.
• Goal-Based Agents: Agents consider their goals and plan actions to
achieve them.
• Utility-Based Agents: Agents evaluate different actions based on a
utility function to determine the most desirable one.
• Learning Agents: Agents improve their performance over time through
learning from experience.

9. Agent-Environment Framework
• Introduce the notion of the agent-environment framework.
• Explain how an agent perceives the environment, processes the
information, selects actions, and receives feedback

10. Examples of Agents and Environments
A self-driving car:
What is peas for a self driving car?
• Performance : safety, time, legal drive, comfort.
• Environment : Roads, other cars, road signs.
• Actuator : Steering, accelerator, break, indicator, horn.
• Sensor: Camera, GPS, speedometer, odometer, engine sensor