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AI3391 ARTIFICAL INTELLIGENCE
(II YEAR (III Sem))
Department of Artificial Intelligence and Data Science
Session 4
by
Asst.Prof.M.Gokilavani
NIET
11/14/2023 Department of AI & DS 1
TEXTBOOK:
• Artificial Intelligence A modern Approach, Third Edition, Stuart
Russell and Peter Norvig, Pearson Education.
REFERENCES:
• Artificial Intelligence, 3rd Edn, E. Rich and K.Knight (TMH).
• Artificial Intelligence, 3rd Edn, Patrick Henny Winston, Pearson
Education.
• Artificial Intelligence, Shivani Goel, Pearson Education.
• Artificial Intelligence and Expert Systems- Patterson, Pearson
Education.
11/14/2023 Department of AI & DS 2
Topics covered in session 4
11/14/2023 Department of AI & DS 3
Unit I: Intelligent Agent
• Introduction to AI
• Agents and Environments
• Concept of Rationality
• Nature of environment
• Structure of Agents
• Problem solving agents
• Search Algorithm
• Uniform search Algorithm
Structure of an AI Agent
• The task of AI is to design an agent program which implements the
agent function.
• The structure of an intelligent agent is a combination of architecture
and agent program.
• It can be viewed as:
11/14/2023 Department of AI & DS 4
Following are the main three terms involved in the structure of an AI
agent:
• Architecture: Architecture is machinery that an AI agent executes on.
• Agent Function: Agent function is used to map a percept to an action.
• Agent program: Agent program is an implementation of agent
function. An agent program executes on the physical architecture to
produce function f.
11/14/2023 Department of AI & DS 5
PEAS Representation
• PEAS is a type of model on which an AI agent works upon. When
we define an AI agent or rational agent, then we can group its
properties under PEAS representation model. It is made up of
four words:
• P: Performance measure
• E: Environment
• A: Actuators
• S: Sensors
• Here performance measure is the objective for the success of an
agent's behavior.
11/14/2023 Department of AI & DS 6
Example: PEAS for self-driving cars
Let's suppose a self-driving car then PEAS representation will be:
• Performance: Safety, time, legal drive, comfort
• Environment: Roads, other vehicles, road signs, pedestrian
• Actuators: Steering, accelerator, brake, signal, horn
• Sensors: Camera, GPS, speedometer, odometer, accelerometer, sonar.
11/14/2023 Department of AI & DS 7
Other Example of Agent
11/14/2023 Department of AI & DS 8
Topics to be covered in next session 5
• Problem Solving Agents
11/14/2023 Department of AI & DS 9
Thank you!!!

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AI3391 ARTIFICAL INTELLIGENCE Session 4 Structure of agent .pptx

  • 1. AI3391 ARTIFICAL INTELLIGENCE (II YEAR (III Sem)) Department of Artificial Intelligence and Data Science Session 4 by Asst.Prof.M.Gokilavani NIET 11/14/2023 Department of AI & DS 1
  • 2. TEXTBOOK: • Artificial Intelligence A modern Approach, Third Edition, Stuart Russell and Peter Norvig, Pearson Education. REFERENCES: • Artificial Intelligence, 3rd Edn, E. Rich and K.Knight (TMH). • Artificial Intelligence, 3rd Edn, Patrick Henny Winston, Pearson Education. • Artificial Intelligence, Shivani Goel, Pearson Education. • Artificial Intelligence and Expert Systems- Patterson, Pearson Education. 11/14/2023 Department of AI & DS 2
  • 3. Topics covered in session 4 11/14/2023 Department of AI & DS 3 Unit I: Intelligent Agent • Introduction to AI • Agents and Environments • Concept of Rationality • Nature of environment • Structure of Agents • Problem solving agents • Search Algorithm • Uniform search Algorithm
  • 4. Structure of an AI Agent • The task of AI is to design an agent program which implements the agent function. • The structure of an intelligent agent is a combination of architecture and agent program. • It can be viewed as: 11/14/2023 Department of AI & DS 4
  • 5. Following are the main three terms involved in the structure of an AI agent: • Architecture: Architecture is machinery that an AI agent executes on. • Agent Function: Agent function is used to map a percept to an action. • Agent program: Agent program is an implementation of agent function. An agent program executes on the physical architecture to produce function f. 11/14/2023 Department of AI & DS 5
  • 6. PEAS Representation • PEAS is a type of model on which an AI agent works upon. When we define an AI agent or rational agent, then we can group its properties under PEAS representation model. It is made up of four words: • P: Performance measure • E: Environment • A: Actuators • S: Sensors • Here performance measure is the objective for the success of an agent's behavior. 11/14/2023 Department of AI & DS 6
  • 7. Example: PEAS for self-driving cars Let's suppose a self-driving car then PEAS representation will be: • Performance: Safety, time, legal drive, comfort • Environment: Roads, other vehicles, road signs, pedestrian • Actuators: Steering, accelerator, brake, signal, horn • Sensors: Camera, GPS, speedometer, odometer, accelerometer, sonar. 11/14/2023 Department of AI & DS 7
  • 8. Other Example of Agent 11/14/2023 Department of AI & DS 8
  • 9. Topics to be covered in next session 5 • Problem Solving Agents 11/14/2023 Department of AI & DS 9 Thank you!!!