ICT619 Intelligent Systems

ICT619 Intelligent SystemsICT619 Intelligent Systems

Topic 8: Intelligent AgentsTopic 8: Intelligent Agents

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Intelligent AgentsIntelligent Agents

What is an intelligent agent?What is an intelligent agent? Why intelligent agents?Why intelligent agents? What intelligent agents can do for usWhat intelligent agents can do for us Characteristics of a good agentCharacteristics of a good agent Types of agentsTypes of agents Building intelligent agentsBuilding intelligent agents Intelligent agents in E-CommerceIntelligent agents in E-Commerce Intelligent agent design - state-of-the-art Intelligent agent design - state-of-the-art

and futureand future

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What is an intelligent agent?What is an intelligent agent?Underlying concept - Underlying concept - An autonomous computational entity designed to perform a An autonomous computational entity designed to perform a

specific task, without direct initiation and continuous monitoring on specific task, without direct initiation and continuous monitoring on part of the userpart of the user

Emerged in the last 15 years or soEmerged in the last 15 years or so Distinct from conventional programs, in that it is Distinct from conventional programs, in that it is automaticautomatic

Additional properties:Additional properties: Some level of intelligence (based on any AI technology from fixed Some level of intelligence (based on any AI technology from fixed

rules to learning engines) for decisions and/or adaptation to rules to learning engines) for decisions and/or adaptation to environmental change environmental change

Acts reactively, but also proactively Acts reactively, but also proactively Social ability - communicates with user, system, other agents as Social ability - communicates with user, system, other agents as

required required Might cooperate with other agents to carry out complex tasksMight cooperate with other agents to carry out complex tasks Agents might move from one system to another to access remote Agents might move from one system to another to access remote

resources and/or meet other agentsresources and/or meet other agents

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What is an intelligent agent? (cont’d)What is an intelligent agent? (cont’d)

Intelligent agents (also called “software agents”) do not Intelligent agents (also called “software agents”) do not necessarily possess necessarily possess allall these possible features these possible features

Wide range of variation in capabilities:Wide range of variation in capabilities:

Some perform tasks individually while others are cooperativeSome perform tasks individually while others are cooperative Some are mobile- able to move across a network, others are notSome are mobile- able to move across a network, others are not

Most communicate via coded messages or even natural Most communicate via coded messages or even natural language, some don't communicate at alllanguage, some don't communicate at all

Multiple agentsMultiple agents work in groups or swarms to solve problems work in groups or swarms to solve problems collectively, some work as individual units collectively, some work as individual units

Not all agents learn and adapt themselvesNot all agents learn and adapt themselves

Robots are physically embodied agentsRobots are physically embodied agents

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Why intelligent agents? Why intelligent agents? More and more everyday tasks becoming computer-basedMore and more everyday tasks becoming computer-based An increasing number of untrained users using computersAn increasing number of untrained users using computers Current human-computer interfaces require users to initiate all Current human-computer interfaces require users to initiate all

tasks and monitor them - manuallytasks and monitor them - manually

Intelligent agents engage in a cooperative process with the user to Intelligent agents engage in a cooperative process with the user to leverage the effectiveness and efficiency of human-computer leverage the effectiveness and efficiency of human-computer interactioninteraction

Staggering growth in information availabilityStaggering growth in information availability Intelligent agents can be a tool for relieving the user of this Intelligent agents can be a tool for relieving the user of this

information overloadinformation overload Intelligent agents can act as personal assistants to the user to Intelligent agents can act as personal assistants to the user to

manage informationmanage information Might one day take over routine tasks in personal management Might one day take over routine tasks in personal management

such as appointments, meetings and travel arrangementssuch as appointments, meetings and travel arrangements

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What intelligent agents can do for usWhat intelligent agents can do for us Carry out tasks on the user’s behalfCarry out tasks on the user’s behalf Train or teach the userTrain or teach the user Help different users collaborateHelp different users collaborate Monitor events and proceduresMonitor events and procedures

Specifically, intelligent agents can help us withSpecifically, intelligent agents can help us with Information retrievalInformation retrieval Information filteringInformation filtering Mail managementMail management Recreational activities – selection of Recreational activities – selection of

books, music, holidaysbooks, music, holidays Booking of meetings, hotels, ticketsBooking of meetings, hotels, tickets

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What intelligent agents can do for us What intelligent agents can do for us (cont’d)(cont’d)

Information filtering agentInformation filtering agent One type is the selection of articles from a continuous One type is the selection of articles from a continuous

stream to suit particular user needsstream to suit particular user needs

User can create “news agents” and train them by giving User can create “news agents” and train them by giving positive or negative feedback for articles recommendedpositive or negative feedback for articles recommended

The use of key words alone can be restrictiveThe use of key words alone can be restrictive Underlying semantics must be extracted for more Underlying semantics must be extracted for more

effectivenesseffectiveness Eg VPOP Technologies' Newshub - an automated, Eg VPOP Technologies' Newshub - an automated,

agent-based web news feeder service, which delivers agent-based web news feeder service, which delivers customised updates of stories from major news outlets customised updates of stories from major news outlets every 15 minutesevery 15 minutes

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Electronic mail agent Electronic mail agent Assist users with electronic mailAssist users with electronic mail Learn to prioritize, delete, forward, sort and archive Learn to prioritize, delete, forward, sort and archive

mail messages on behalf of the usermail messages on behalf of the user May use intelligent system techniques like case-based May use intelligent system techniques like case-based

reasoningreasoning Can associate a level of confidence with its action or Can associate a level of confidence with its action or

suggestionsuggestion Use of “do-it” and “tell-me” thresholds set by userUse of “do-it” and “tell-me” thresholds set by user May involve multi-agent collaboration May involve multi-agent collaboration

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Selection agents for entertainmentSelection agents for entertainment Conversational agents show potential for Conversational agents show potential for

becoming popular and commercially becoming popular and commercially successful eg Cybelle, ALICEsuccessful eg Cybelle, ALICE

Use “social filtering” – correlation between different Use “social filtering” – correlation between different users to make recommendations on books, CDs, films users to make recommendations on books, CDs, films etc.etc.

So, if user So, if user AA liked items liked items XX and and YY, and user , and user BB liked item liked item XX and and ZZ, then item , then item ZZ may be recommended for user may be recommended for user AA

Amazon.com has been using this system for years ->Amazon.com has been using this system for years ->

Hi, I am Cybelle.What is your name?

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Some other current and emerging applications of Some other current and emerging applications of intelligent agents:intelligent agents:

air traffic controlair traffic control air craft mission analysisair craft mission analysis control of telecommunications and network systemscontrol of telecommunications and network systems provision and monitoring of medical careprovision and monitoring of medical care monitoring and control of industrial processesmonitoring and control of industrial processes on-line fault diagnosis and malfunction handlingon-line fault diagnosis and malfunction handling supervision and control of manufacturing environmentssupervision and control of manufacturing environments transactions management in banks and insurance transactions management in banks and insurance

companiescompanies E-commerce, tourismE-commerce, tourism

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Characteristics of a good agentCharacteristics of a good agentActionAction Agent must be able to take some action and not just Agent must be able to take some action and not just

provide adviceprovide advice Present state of web technology limits capability of Present state of web technology limits capability of

Internet agents Internet agents - still no standard interface for agents, but agent - still no standard interface for agents, but agent communication languages such as ACL and KQML communication languages such as ACL and KQML might win outmight win out

As the Internet becomes more agent-friendly, more As the Internet becomes more agent-friendly, more capable agents will emergecapable agents will emerge

AutonomyAutonomy An agent can be much more useful if it can act An agent can be much more useful if it can act

autonomouslyautonomously The right level of autonomy for a task must be foundThe right level of autonomy for a task must be found

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Characteristics of a good agent (cont.) Characteristics of a good agent (cont.)

CommunicationCommunication Must communicate well with the userMust communicate well with the user Should understand user’s goals, preferences and constraintsShould understand user’s goals, preferences and constraints Useful communication requires shared knowledge on Useful communication requires shared knowledge on

language of communication language of communication problem domainproblem domain

Example Problem: Web search enginesExample Problem: Web search engines accept key words and phrases (some knowledge of the accept key words and phrases (some knowledge of the

language) language) but but understand nothing about the documents they retrieve (no understand nothing about the documents they retrieve (no

domain knowledge)domain knowledge) Solution: provision of a machine-readable Solution: provision of a machine-readable ontologyontology

- a definition of a body of knowledge including its - a definition of a body of knowledge including its components and their relationships components and their relationships

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Characteristics of a good agent (cont.)Characteristics of a good agent (cont.)

AdaptationAdaptation Can gain user confidence by learning user preferencesCan gain user confidence by learning user preferences ML techniques such as ANNS, GAs or CBR can be ML techniques such as ANNS, GAs or CBR can be

usedused Adapting to user preferences can be also achieved by Adapting to user preferences can be also achieved by

using data mining techniques such as clusteringusing data mining techniques such as clustering Agent forms clusters of users with similar featuresAgent forms clusters of users with similar features User's needs can then be anticipated by placing the User's needs can then be anticipated by placing the

user in one of these clusters and analysing the clusteruser in one of these clusters and analysing the cluster Social problem solving method, similar to Amazon Social problem solving method, similar to Amazon

recommendationsrecommendations

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Types of agentsTypes of agents Based on operational characteristics and Based on operational characteristics and

functional objectives:functional objectives: Collaborative agentsCollaborative agents Work together to Work together to

- integrate information and - integrate information and - negotiate with other agents to resolve conflict- negotiate with other agents to resolve conflict- Provide solutions to inherently distributed problems, - Provide solutions to inherently distributed problems,

e.g., air traffic controle.g., air traffic control

Reactive agentsReactive agents Act by stimulus-response to the current state of Act by stimulus-response to the current state of

the environmentthe environment Each reactive agent is simple and interacts Each reactive agent is simple and interacts

with others in a basic waywith others in a basic way

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Types of agents (cont’d)Types of agents (cont’d)

Interface agentsInterface agents Provide user support and assistanceProvide user support and assistance Cooperate with user in accomplishing some task in an Cooperate with user in accomplishing some task in an

application.application. Interface agents learn: Interface agents learn:

by observing and imitating the user by observing and imitating the user through receiving feedback from the user through receiving feedback from the user by receiving explicit instructions by receiving explicit instructions by asking other agents for advice (from peers) by asking other agents for advice (from peers)

Examples:Examples: Personal assistants performing information filtering, Personal assistants performing information filtering,

email management.email management.

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Types of agents (cont.)Types of agents (cont.)Mobile agentsMobile agents Programs that migrate from one machine to another. Programs that migrate from one machine to another. Execute in a platform-independent execution environment, like Execute in a platform-independent execution environment, like

Java applets running on a Java virtual machine Java applets running on a Java virtual machine Practical but non-functional advantages: Practical but non-functional advantages:

Reduced communication costReduced communication cost Asynchronous computing (when you are not connected)Asynchronous computing (when you are not connected)

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Types of agents (cont.)Types of agents (cont.)

Two types of mobile agents: Two types of mobile agents: One-hop mobile agents (migrates to one other One-hop mobile agents (migrates to one other

place) place) Multi-hop mobile agents (roam the network Multi-hop mobile agents (roam the network

from place to place) from place to place) Example applications: Example applications: Distributed information retrieval Distributed information retrieval Telecommunication network routingTelecommunication network routing

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Information agentsInformation agents Manage information Manage information Manipulate or collate information from many distributed Manipulate or collate information from many distributed

sources. sources. Can be mobile or static. Can be mobile or static. Examples: Examples: BargainFinder compares prices among Internet stores for BargainFinder compares prices among Internet stores for

CDs CDs Jasper works on behalf of a user or community of users and Jasper works on behalf of a user or community of users and

stores, retrieves and informs other agents of useful stores, retrieves and informs other agents of useful information on the WWW information on the WWW

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Multiple agent systemsMultiple agent systems Consist of collections, or swarms, of simple agents that Consist of collections, or swarms, of simple agents that

interact with each other and the problem environmentinteract with each other and the problem environment Can be mobile or static, same or different agents Can be mobile or static, same or different agents Complex patterns of behaviour emerge from collective Complex patterns of behaviour emerge from collective

interactioninteraction Examples: Examples: Swarm of bees finds an optimal location for the hive Swarm of bees finds an optimal location for the hive xxxxxxxx

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Building intelligent agentsBuilding intelligent agents

Two main problems to overcome:Two main problems to overcome:

CompetenceCompetence How do we build agents with the knowledge needed to decide How do we build agents with the knowledge needed to decide

when to help the userwhen to help the user what to help the user with, and what to help the user with, and how to help the user?how to help the user?

TrustTrust How to guarantee user comfort (and protection!) in How to guarantee user comfort (and protection!) in

delegating tasks to the agentdelegating tasks to the agent

Approaches to building agentsApproaches to building agents1.1. User-programmed agents - write specialised scriptsUser-programmed agents - write specialised scripts2.2. Knowledge-based agentsKnowledge-based agents3.3. Machine-learning approachMachine-learning approach

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Building intelligent agents (cont’d)Building intelligent agents (cont’d)

The main problem with The main problem with user-programmeduser-programmed approach approach - requires high level of user competency- requires high level of user competency- user must be able to- user must be able to Recognise opportunity for employing an agentRecognise opportunity for employing an agent Take initiative to create an agent Take initiative to create an agent Impart specific knowledge to agent by codifying it in a Impart specific knowledge to agent by codifying it in a

special languagespecial language Maintain agent’s knowledge by updating rule base with Maintain agent’s knowledge by updating rule base with

timetime

The issue of trust is then reduced to users’ trust in The issue of trust is then reduced to users’ trust in their own programming skillstheir own programming skills

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Building intelligent agents (cont.)Building intelligent agents (cont.)

In the In the knowledge-based approach,knowledge-based approach, The agent is supplied with knowledge about The agent is supplied with knowledge about

the application and userthe application and user

At run-time, agent uses the knowledge to At run-time, agent uses the knowledge to recognise user’s plans and find opportunities recognise user’s plans and find opportunities to contribute to themto contribute to them

Example of knowledge-based agent: the Example of knowledge-based agent: the UCEgo - designed to help users solve UCEgo - designed to help users solve problems in using the UNIX operating system. problems in using the UNIX operating system.

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Building intelligent agents (cont.)Building intelligent agents (cont.)

Problems with knowledge-based approach - Problems with knowledge-based approach - Both competence and trust are issues of concern Both competence and trust are issues of concern

The problem of competence relates to the competence The problem of competence relates to the competence of the knowledge engineerof the knowledge engineer

Knowledge-base is fixed and cannot be customised to Knowledge-base is fixed and cannot be customised to specific user needsspecific user needs

User’s trust is affected as agent is programmed by User’s trust is affected as agent is programmed by someone elsesomeone else

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Building agents – the machine Building agents – the machine learning approachlearning approach

Metaphor of a personal office assistantMetaphor of a personal office assistant Agents start with minimum knowledge and learn Agents start with minimum knowledge and learn

from:from:1.1. Observation and imitation of userObservation and imitation of user2.2. User feedback – direct, indirectUser feedback – direct, indirect3.3. Training by userTraining by user4.4. Other agentsOther agents

User can build up model of agent decision making – User can build up model of agent decision making – more trustmore trust

Agent capable of explanationAgent capable of explanation

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Development of an agent through Development of an agent through learninglearning

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Building agents – the machine Building agents – the machine learning approachlearning approach

Advantages:Advantages: Less work from end-user and developerLess work from end-user and developer Agent customises to user/organisation Agent customises to user/organisation

habits/preferenceshabits/preferences Helps distribute know-how and competence Helps distribute know-how and competence

among different usersamong different users

Some examples:Some examples: Agent for e-mail handlingAgent for e-mail handling Agent for meeting schedulingAgent for meeting scheduling Agent for electronic news filteringAgent for electronic news filtering Agent for recommending books, musicAgent for recommending books, music

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Intelligent agents in E-commerceIntelligent agents in E-commerce Rapid growth continues in e-commerceRapid growth continues in e-commerce Information about products and vendors is easily Information about products and vendors is easily

accessibleaccessible But transactions are still mostly not automatedBut transactions are still mostly not automated

Six fundamental stages of the buying process:Six fundamental stages of the buying process: Need identificationNeed identification Product brokeringProduct brokering Merchant brokeringMerchant brokering NegotiationNegotiation Purchase and deliveryPurchase and delivery Product service and evaluationProduct service and evaluation

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Intelligent agents in E-Commerce Intelligent agents in E-Commerce (cont’d)(cont’d)

In the need-identification stage, agents can help in In the need-identification stage, agents can help in purchases that are repetitive or predictablepurchases that are repetitive or predictable

Continuously running agents can monitor a set of Continuously running agents can monitor a set of sensors or data streams and take actions when certain sensors or data streams and take actions when certain pre-specified conditions applypre-specified conditions apply

Agents can use rule-based systems or data mining Agents can use rule-based systems or data mining techniques to discover patterns in customer behaviour techniques to discover patterns in customer behaviour to help customers find productsto help customers find products

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Intelligent agents in E-commerce Intelligent agents in E-commerce (cont.)(cont.)

In the merchant brokering stage, on-line In the merchant brokering stage, on-line shopping agents can look up prices for a shopping agents can look up prices for a chosen product for a number of merchantschosen product for a number of merchants

Many business-to-business transactions are Many business-to-business transactions are canvassedcanvassed

In a web auction, customers are required to In a web auction, customers are required to manage their own negotiation strategiesmanage their own negotiation strategies

Intelligent agents can help with thisIntelligent agents can help with this

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Examples of on-line shopping Examples of on-line shopping

framework with agent mediationframework with agent mediation PERSONA PERSONA LogicLogic

FireflyFirefly Bargain Bargain FinderFinder

Auction Auction

BotBot

JangoJango Auction Auction BotBot

T@TT@T

Need Need identificationidentification

Product Product brokeringbrokering

** ** ** **

Merchant Merchant brokeringbrokering

** ** **

NegotiationNegotiation ** ** **Payment & Payment & deliverydelivery

Service & Service & EvaluationEvaluation

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framework with agent mediationframework with agent mediation

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framework with agent mediationframework with agent mediation

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Examples of on-line shopping framework Examples of on-line shopping framework with agent mediation (cont’d)with agent mediation (cont’d)

Software agents are helping buyers and sellers cope Software agents are helping buyers and sellers cope with information overload and expedite the online with information overload and expedite the online buying processbuying process

Agents are creating new markets (eg, low-cost Agents are creating new markets (eg, low-cost consumer goods) and reducing transaction costsconsumer goods) and reducing transaction costs

Use of agents in e-commerce still at an early stageUse of agents in e-commerce still at an early stage

Visit Visit http://agents.umbc.edu/Applications_and_Software/Aphttp://agents.umbc.edu/Applications_and_Software/Applications/Electronic_Commerce/index.shtmlplications/Electronic_Commerce/index.shtmlfor morefor more

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Intelligent agent design - state-of-the-Intelligent agent design - state-of-the-art and future art and future

Few agents are available with all the desired Few agents are available with all the desired characteristicscharacteristics

Agent technology still in experimental stageAgent technology still in experimental stage

Autonomy and mobility already achievableAutonomy and mobility already achievable

Example: Java applets which execute independently Example: Java applets which execute independently across networksacross networks

But autonomy limited so far in practical use due to the But autonomy limited so far in practical use due to the agent-unfriendliness of the current web technologyagent-unfriendliness of the current web technology

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Intelligent agent design - state-of-the-Intelligent agent design - state-of-the-art and future (cont’d)art and future (cont’d)

A major limiting factor is lack of ontologies A major limiting factor is lack of ontologies essential for effective communicationessential for effective communication

Building and maintaining ontologies remains a Building and maintaining ontologies remains a major challenge major challenge

Some of the proposed capabilities to be Some of the proposed capabilities to be developed in future intelligent agents include:developed in future intelligent agents include: Learning as well as reasoning, which are Learning as well as reasoning, which are

characteristics of machine intelligencecharacteristics of machine intelligence Interacting with the external environment through Interacting with the external environment through

sensorssensors

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REFERENCESREFERENCES Chin, D.,Chin, D., Intelligent Interfaces as Agents. In Intelligent Interfaces as Agents. In Intelligent User Intelligent User

InterfacesInterfaces, J. Sullivan and S. Tyler(eds), ACM Press, New , J. Sullivan and S. Tyler(eds), ACM Press, New York, 1991.York, 1991.

Hendler, J., Hendler, J., Making Sense out of AgentsMaking Sense out of Agents, IEEE Intelligent , IEEE Intelligent Systems, March/April 1999, pp.32-37.Systems, March/April 1999, pp.32-37.

Hendler, J., Hendler, J., Is There an intelligent Agent in Your Future? Is There an intelligent Agent in Your Future? http//www.nature.com/nature/webmatters/agents/agents.htmlhttp//www.nature.com/nature/webmatters/agents/agents.html

Maes, P., Maes, P., Agents that Reduce Work and Information Agents that Reduce Work and Information OverloadOverload, Communications of the ACM, Volume 37 , Issue 7 , Communications of the ACM, Volume 37 , Issue 7 (July 1994), (July 1994), pp.pp. 30-40. 30-40.

Maes, P., Maes, P., Agents that Buy and SellAgents that Buy and Sell, Communications of the , Communications of the ACM, Volume 42 , Issue 3 (March 1999), ACM, Volume 42 , Issue 3 (March 1999), pp.pp. 81-91. 81-91.

Sheth, B. and Maes, P. Evolving Agents for Personalized Sheth, B. and Maes, P. Evolving Agents for Personalized Information Filtering. In Proceedings of the Ninth Conf. on Information Filtering. In Proceedings of the Ninth Conf. on Artificial Intelligence for Applications. IEEE Computer Society Artificial Intelligence for Applications. IEEE Computer Society Press, 1993Press, 1993

UMBC Agent News - UMBC Agent News - http://http://agents.umbc.edu/agentnews/currentagents.umbc.edu/agentnews/current// http://www.agentland.com/http://www.agentland.com/

ICT619 Intelligent Systems

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