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E-Learning

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E-Learning

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  1. E-Learning Intelligent Agents and E-Business

  2. Intelligent Agents • What are they? • How do they work? • Why e-business? • Assumptions • Summary

  3. What is an agent? • Human agent or assistant • travel agent • estate agent • secret agent • Focus on a task • Specialist skills • Access to relevant information • Contacts to provide service, can provide it at fraction of cost • Can only work < 84 hours per week

  4. What can an agent do? • Provide information & description of a service or product • Locate best sources, companies, locations • Find best prices • Negotiate agreement between purchaser and supplier • Prepare & distribute documents, contracts, agreements

  5. What can an agent do cont. • Monitor results and resolve problems • Provide additional information and clarification • Collect revenue, fees, commissions & distribute funds • Terminate service/product if no payment • Send out renewals & reminders

  6. House Seller House Buyer Example Solicitors Buying Agent Selling Agent

  7. What are intelligent agents? • software or hardware applications • undertake tasks on behalf of user • possess some knowledge • may incorporate a learning system • use reasoning to achieve user’s goals • Simple example: • email filter - directs emails into folders automatically based on certain pre-defined criteria

  8. Intelligent agents cont. • Agents typically act independently of each other • learn and adapt from actions or the environment • can be mobile • Categorised using three dimensions: • Agency • Intelligence • Mobility

  9. Agency • ‘Degree of independence’ • knowing the user’s goals, must be able to accomplish a mission without human intervention • need to communicate with data repositories and other agents • increased sophistication allows cooperation between agents, sharing knowledge and objectives to solve common goals

  10. Intelligence • Ability to reason using current knowledge of user as well as past experiences • Could be rule-based; • reasoned against a set of pre-defined conditions • Knowledge-based; • data relating to prior situations and resulting actions supplied to agent, on which it bases its decisions

  11. Mobility • Agents can be static, working in one computer • Can also travel across networks, gathering information • Some travel from computer to computer, returning to host only when all search conditions are met • Others travel between client and server (more secure)

  12. Other Attributes • Act in the best interests of the user • must not injure a human, or through inaction allow a human to come to harm • must obey orders given by humans except where such orders conflict with the first law • must protect its own existence as long as such protection does not conflict with the 1st and 2nd laws

  13. How do they know what to do? • User programmed approach • needs to represent own knowledge in a programming language • Knowledge-based approach • provide agent with user and domain (environment) knowledge • difficult to customise - generic solution • Learning approach • minimum background information • learns from user and other agents • behaviour must be repetitive

  14. Recap 1. PA not familiar with habits/systems of new employer - not very helpful on day one 2. PA needs time to become familiar with working methods 2. Agent needs either pre-defined knowledge base or time to learn 1. Agent is ignorant 3. PA Learns by watching employer perform tasks, receiving instructions/training and learning from other PAs 4. More tasks performed by employer are taken over by the PA 4. Agent adapts and becomes more autonomous 3. Agent interacts with user and other agents

  15. How do they work? • Develop a user profile • where you visit • what you read/watch/contribute • Learn • how user evolves • how similar users evolve

  16. How do they communicate? • Need a common transport protocol • messages sent by one party must be understood by others • TCP/IP • Can use HTML to exchange information

  17. How do they work? Client allowed to store procedures, instructions and data on server Client accesses agent via browser on workstation HTML message sent via TCP/IP User profile stored on client or server - depending on system architecture Data on client - less network traffic, but data could be lost Data on server - more traffic, data backed-up, but DPA and hacking/misuse issues

  18. What have they got to do with e-business? • Buyer agents • personal shopper • reduced effort - ‘Let your fingers do the walking’, Yellow Pages • comparing prices while you sleep • Seller agents • target your market more effectively • dynamic market research, knowledge mining • learn from customers and personalise

  19. Assumptions • Design • need to incorporate open design to allow continuous development • Quality of Databases • quality of content across the web is extremely variable as are standards • sites need some authentication for trustworthiness • need consistent data standards - XML

  20. Assumptions 2 • Functionality • optimum benfits derived when intelligence gathering is incorporated • Friendly environment • for multi-agent environments, hosts must allow agent scripts to live and work remotely • must converse with visiting agents • web security a major issue

  21. Summary • What are they? • human and software agents • How do they work? • agency, mobility, system architecture, profiles • Why e-business? • buying, selling, market research • Assumptions • standards, databases, remote working, security