A.i lecture 04

Artificial Intelligence
Imran yar
BSC,MCS
Lecturer of CS

• Weak and Strong AI
• Acting humanly
• Think like humans
• think rationally
• Acting rationally
• Turing Test
• Chinese Room Argument
Summary of Previous Lecture

Today’s Lecture
• What is an Intelligent agent?
• Agents & Environments
• Performance measure
• Environment
• Actuators
• Sensors
• Features of intelligent agents

Ability to Exist to be Autonomous, Reactive,
Goal-Oriented, etc.
- are the basic abilities of an Intelligent Agent

What is an Intelligent agent?
• “Agent” can be considered as a theoretical
concept from AI.
• Many different definitions exist in the
literature…..

Agent Definition (1)
• An agent is an entity which is:
– Situated in some environment.
– Autonomous, in the sense that it can act without direct intervention
from humans or other software processes, and controls over its own
actions and internal state.
– Flexible which means:
• Responsive (reactive): agents should perceive their environment
and respond to changes that occur in it;
• Proactive: agents should not simply act in response to their
environment, they should be able to exhibit opportunistic, goal-
directed behavior and take the initiative when appropriate;
• Social: agents should be able to interact with humans or other
artificial agents
“A Roadmap of agent research and development”,
N. Jennings, K. Sycara, M. Wooldridge (1998)

American Heritage Dictionary:
agent-
” … one that acts or has the power or
authority to act… or represent
another”

• "An agent is anything that can be viewed
as perceiving its environment through
sensors and acting upon that
environment through effectors."
Russell & Norvig

• “Intelligent agents continuously perform
three functions: perception of dynamic
conditions in the environment; action to
affect conditions in the environment; and
reasoning to interpret perceptions, solve
problems, draw conclusions, and
determine actions.”
Barbara Hayes-Roth

Agents & Environments
 The agent takes sensory input from its
environment, and produces as output actions
that affect it.
Environment
sensor
input
action
outputAgent

Internal and External Environment of
an Agent
Internal Environment:
architecture, goals, abilities, sensors,
effectors, profile, knowledge,
beliefs, etc.
External Environment:
user, other humans, other agents,
applications, information sources,
their relationships,
platforms, servers, networks, etc.
Balance

Overall Intelligent Agent
[Terziyan, 1993]
1) is goal-oriented, because it should have at least one goal -
to keep continuously balance between its internal and external
environments ;
2) is creative because of the ability to change external environment;
3) is adaptive because of the ability to change internal environment;
4) is mobile because of the ability to move to another place;
5) is social because of the ability to communicate to create a
community;
6) is self-configurable because of the ability to protect “mental
health” by sensing only a “suitable” part of the environment.

Three groups of agents
[Etzioni and Daniel S. Weld, 1995]
• Backseat driver: helps the user during some task
(e.g., Microsoft Office Assistant);
• Taxi driver: knows where to go when you tell the
destination;
• Caretaker : know where to go, when and why.

Agent’s function maps
• The agent function maps from percept histories to actions:

Agents example
• Human agent:
– eyes, ears, and other organs for sensors;
– hands, legs, mouth, and other body parts for actuators
• Robotic agent:
– cameras and infrared range finders for sensors
– various motors for actuators

PEAS
• Use PEAS to describe task environment
– Performance measure
– Environment
– Actuators
– Sensors
• Example: Taxi driver
– Performance measure: safe, fast, comfortable
(maximize profits)
– Environment: roads, other traffic, pedestrians,
customers
– Actuators: steering, accelerator, brake, signal, horn
– Sensors: cameras, sonar, speedometer, GPS,
odometer, accelerometer, engine sensors

PEAS
• Agent: Part-picking robot
• Performance measure: Percentage of parts in
correct boxes
• Environment: Conveyor belt with parts, boxes
• Actuators: Jointed arm and hand
• Sensors: Camera, joint angle sensors

PEAS
• Agent: Medical diagnosis system
• Performance measure: Healthy patient, minimize
costs, lawsuits
• Environment: Patient, hospital, staff
• Actuators: Screen display (questions, tests,
diagnoses, treatments, referrals)
•
• Sensors: Keyboard (entry of symptoms, findings,
patient's answers)

PEAS
• Agent: Interactive English tutor
• Performance measure: Maximize student's
score on test
• Environment: Set of students
• Actuators: Screen display (exercises,
suggestions, corrections)
• Sensors: Keyboard

Agents and Their Actions
a rational agent does “the right thing”
 the action that leads to the best outcome under the
given circumstances
an agent function maps percept sequences to
actions
 abstract mathematical description
an agent program is a concrete implementation
of the respective function
 it runs on a specific agent architecture (“platform”)

Description of Agent‘s character
 An agent is responsible for satisfying specific goals. There can
be different types of goals such as achieving a specific status,
maximising a given function (e.g., utility), etc.
 The state of an agent includes state of its internal
environment + state of knowledge and beliefs about its
external environment.
knowledge
beliefs
Goal1
Goal2

Connections
• An agent is situated in an environment, that consists of
the objects and other agents it is possible to interact
with.
• An agent has an identity that distinguishes it from the
other agents of its environment.
environment

Summery of Today’s Lecture
• What is an Intelligent agent?
• Agents & Environments
• Performance measure
• Environment
• Actuators
• Sensors
• Features of intelligent agents

A.i lecture 04

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