1. EA C461 – Artificial Intelligence Intelligent Agents
S.P.Vimal

2. To discuss… Agents Rational Agents Task Environments
Vimal EA C461- Artificial Intelligence

3. Agent
“An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators”
“An agent’s choice of action at any given instant can depend on the entire percept sequence observed to date”
Percept sequence  Complete history of everything the agent have ever perceived
Vimal EA C461- Artificial Intelligence

4. Agent
An agents behavior is described by agent function, mapping of any given percept sequence to an action
An agent program internally implements the artificial agent’s agent function
Vimal EA C461- Artificial Intelligence

5. A Simple Intelligent Agent
Percept Sequence
Action
[A, Clean]
Right
[A, Dirty]
Suck
[B, Clean]
Left
[B, Dirty]
[A, Clean], [A, Clean]
[A, Clean], [A, Dirty] …
[A, Clean], [A, Clean] ,[A, Clean]
[A, Clean], [A, Clean] , [A, Dirty]
Percepts: location and contents, e.g., [A, Dirty]
Actions: Left, Right, Suck, NoOp
Simple Agent Function
Vimal EA C461- Artificial Intelligence

6. Good behavior (being Rational)
agreeable to reason; reasonable; sensible: a rational plan for economic development.
having or exercising reason, sound judgment, or good sense: a calm and rational negotiator.
being in or characterized by full possession of one's reason; sane; lucid: The patient appeared perfectly rational.
endowed with the faculty of reason: rational beings.
of, pertaining to, or constituting reasoning powers: the rational faculty.
proceeding or derived from reason or based on reasoning: a rational explanation. …
Vimal EA C461- Artificial Intelligence

7. Good behavior (being Rational)
A rational agent is the one that does the right thing
Right action is the one that cause the agent to be more successful
Appropriate performance measures for the vacuum world
Amount of dirt cleaned in a duration
Clean squares at ever time slots
How do we say an action is rational at a given point of time?
Vimal EA C461- Artificial Intelligence

8. Rational Agents
For each possible percept sequence, a rational agent should select an action that is expected to maximize it’s performance measure ,given the evidence provided by the percept sequence and whatever the built-in knowledge, the agent has.
Is our Vacuum Cleaner Agent rational?
Vimal EA C461- Artificial Intelligence

9. Rational Agents Is an omniscient agent rational? Learning  autonomy
Maximizing actual performance Vs. Maximizing expected performance
Learning  autonomy
A rational agent is autonomous
Learn to compensate for partial / incorrect knowledge
Vimal EA C461- Artificial Intelligence

10. Task Environment
Task environments are “problems” for which the rational agents are the “solutions”
Includes
Performance measure
Environment
Actuator
Sensors
Vimal EA C461- Artificial Intelligence

11. Task Environment Agent Type Performance Measures Environment Actuators
Sensors
Taxi Driver
Safe, Fast, Legal, Comfort, Maximize Profits
Roads, other traffic, pedestrians, customers
Steering, accelerators, brake, signal, horn
Camera, sonar, GPS, Speedometer, keyboard, etc
Medical diagnosis system
Healthy patient, minimize costs, lawsuits
Patient, hospital, staff
Screen display (questions, tests, diagnoses, treatments, referrals)
Keyboard (entry of symptoms, findings, patient's answers)
PEAS Descriptions
Vimal EA C461- Artificial Intelligence

12. Properties of Task Environment
Fully Observable (vs. Partly Observable)
Agent sensors give complete state of the environment at each point in time
Sensors detect all the aspect that are relevant to the choice of action
Deterministic (vs. Stochastic)
Next state of the environment is completely determined by the current state and the action executed by the agent
Strategic environment
Vimal EA C461- Artificial Intelligence

13. Properties of Task Environment
Episodic (vs. Sequential)
Agent’s experience can be divided into episodes, each episode with what an agent perceive and what is the action
Next episode does not depend on the previous episode
Current decision will affect all future sates in sequential environment
Static (vs. Dynamic)
Environment doesn’t change as the agent is deliberating
Semi dynamic
Vimal EA C461- Artificial Intelligence

14. Properties of Task Environment
Discrete (vs. Continuous)
Depends the way time is handled in describing state, percept, actions
Chess game : discrete
Taxi driving : continuous
Single Agent (vs. Multi Agent)
Competitive, cooperative multi-agent environments
Communication is a key issue in multi agent environments
Vimal EA C461- Artificial Intelligence

15. Task Environment Chess with a clock Chess without a clock Taxi Driving
Fully observable
Deterministic
Episodic
Static
Discrete
Single agent
Example of Task Environments and Their Classes
Vimal EA C461- Artificial Intelligence

16. Structure of Agents Agent = Architecture + Program
Implements Agent Function, performs mapping of percepts to actions
Computing device Running Agent Program, with sensors & actuators
Vimal EA C461- Artificial Intelligence

17. Vimal EA C461- Artificial Intelligence