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