Intelligent Agent PPT ON SLIDESHARE IN ARTIFICIAL INTELLIGENCE

n artificial intelligence, an intelligent agent (IA) is an autonomous entity which acts, directing its activity towards achieving goals (i.e. it is an agent), upon an environment using observation through sensors and consequent actuators (i.e. it is intelligent).An intelligent agent is a program that can make decisions or perform a service based on its environment, user input and experiences. These programs can be used to autonomously gather information on a regular, programmed schedule or when prompted by the user in real time. Intelligent agents may also be referred to as a bot, which is short for robot.Examples of intelligent agents
AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. They can be used to gather information about its perceived environment such as weather and time.

Infogate is another example of an intelligent agent, which alerts users about news based on specified topics of interest.

Autonomous vehicles could also be considered intelligent agents as they use sensors, GPS and cameras to make reactive decisions based on the environment to maneuver through traffic.



Examples of intelligent agents
AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. They can be used to gather information about its perceived environment such as weather and time.

Infogate is another example of an intelligent agent, which alerts users about news based on specified topics of interest.

Autonomous vehicles could also be considered intelligent agents as they use sensors, GPS and cameras to make reactive decisions based on the environment to maneuver through traffic.

1. Created By-
Khushboo Pal
B.Tech (Computer Science & Engineering)

2. InstructionalObjectives
Define anagent.
Agents Classification.
Define an Intelligentagent.
Define a Rationalagent.
Explain classes or Types of
intelligentagents
Applications of Intelligentagent

3. Agents
Anagentisanythingthatcanbeviewedas
perceivingitsenvironmentthroughsensorsand
actinguponthatenvironmentthrougheffectors.
Ahumanagenthaseyes,ears,andotherorgansfor
sensors,andhands,legs,mouth,andotherbody
partsforeffectors/actuators.
Aroboticagentsubstitutescamerasandinfrared
rangefindersforthesensorsandvariousmotorsfor
theeffectors.

4. Agents
Operate in anenvironment.
Perceivesandacts upon it'senvironment
throughactuators/sensorsand have its goals.
.

5. Agent andEnvironment

6. Sensors &Effectors
AnagentPerceivesitsenvironmentthrough
sensors.
Thecompletesetofinputsatagiventimeiscalled
percept.
Thecurrentpercept,orasequenceofperceptscan
influencetheactionsofanagent.
Itcanchangetheenvironmentthrough
effectors.
Anoperationinvolvinganactuatoris called
anaction ,which can be groupedinto action
sequences.

7. AgentsClassification
.

8. Examples ofagents
Humans
eyes, ears, skin, taste buds, etc. forSensors.
hands, fingers, legs, mouth foreffectors.
etc.for
Robots
camera,infrared,bumper,etc.forsensors.
grippers,wheels,lights,speakers,effectors.

9. Structure ofagents
Asimpleagentprogramcanbedefined
mathematicallyasanagentfunctionwhich
mapseverypossiblepreceptssequencetoa
possibleactiontheagentcanperform.
F: p*->A
thetermperceptisusetotheagent's
perceptionalinputsatanygiveninstant.

10. Intelligentagents
Fundamental functionalitiesof
intelligence Actingare:
Sensing
Understanding, Reasoning,learning
In order to actyou must sense. Blind actions isnot
a characterization ofintelligence.
Robotics: sensingand acting.
Understandingnot necessary.
Sensing needs understanding to beuseful.

11. IntelligentAgents
IntelligentAgent:
must sense,
mustact,
must be rational,
and autonomous.

12. RationalAgent
AI is about building rationalagents.
Anagentissomethingthatperceives and
acts.
Arationalagentalwaysdoestheright
thingas-
What are the Functionalities ?(Goals)
What are the components?
How do we build them?

14. Rationality
PerfectRationality:
Assumesthattherationalagentknows
allandwilltaketheactionthatmaximize
theutility.
Humanbeingsdonotsatisfythis
definitionofrationality.

15. AgentEnvironment
Environmentsinwhichagentsoperate
canbedefinedindifferentways.
Itishelpfultoviewthefollowing
definitionsasreferringtothewaythe
environmentappearsfromthepointof
viewoftheagentitself.

16. Classes of Intelligent
Agents
Intelligentagentsaregroupedintofive
classesbasedontheirdegreeofperceived
intelligenceandcapability.
Simplereflexagents
Modelbasedreflexagents
Goalbasedagents
Utilitybasedagents
Learningagents

17. 1.Simple reflexagents
Simplereflexagentsactonlyonthebasisofthe
currentpercept,ignoringtherestofthepercept
history.Theagentfunctionisbasedonthecondition-
actionrule:ifconditionthenaction.
Succeedswhentheenvironmentisfullyobservable.
Somereflexagentscanalsocontaininformationon
theircurrentstatewhichallowsthemtodisregard
conditions.

18. Simple reflexagents

19. 2. Model based reflex
agents
Amodel-basedagent can
handle apartially observable
environment.
Thisknowledgeabout"howtheworld
evolves"iscalledamodeloftheworld,
hencethename"model-basedagent".

20. Model based reflex
agents

21. 3.Goal basedagents
Goal-basedagentsfurtherexpandonthe
capabilitiesofthemodel-basedagents,byusing
"goal"information.
Goalinformationdescribessituationsthatare
desirable.Thisallowstheagentawaytochoose
amongmultiplepossibilities,selectingtheone
whichreachesagoalstate.
Searchandplanningarethesubfieldsofartificial
intelligencedevotedtofindingactionsequences
thatachievetheagent'sgoals.

22. Goal basedagents

23. 4. Utility basedagents
Goal-basedagentsonlydistinguishbetweengoalstates
andnon-goalstates.
Itispossibletodefineameasureofhowdesirablea
particularstateis.Thismeasurecanbeobtainedthrough
theuseofautilityfunctionwhichmapsastatetoa
measureoftheutilityofthestate.
A more general performance measure should allow a
comparison of different world states according to exactly
how happy they would make the agent. The term utility,
can be used to describe how "happy" the agent is.

24. Utility basedagents

25. 5. Learningagents
Learninghasanadvantagethatitallowstheagentsto
initiallyoperateinunknownenvironmentsandtobecome
morecompetentthanitsinitialknowledgealonemight
allow.
Themostimportantdistinctionisbetweenthe"learning
element",whichisresponsibleformakingimprovements,
andthe"performanceelement",whichisresponsiblefor
selectingexternalactions.
Thelearningelementusesfeedbackfromthe"critic"on
howtheagentisdoinganddetermineshowthe
performanceelementshouldbemodifiedtodobetterinthe
future.

26. Learningagents
Thelastcomponentofthelearningagentis
the"problemgenerator".Itisresponsiblefor
suggestingactionsthatwillleadtonewand
informativeexperiences.

27. Applications of
Intelligent Agents
Intelligentagentsareappliedas
automated online assistants, as
Where they function to perceive the needs of
Customers in order to perform individualized
customerservice.
Use in smart phones infuture.