Agent Technology Diffusion National Roadshow

1. Agent Technology DiffusionNational Roadshow Canberra May 24, 2000

2. Overview • Context • The excitement of agents • Coffee break • The definition of agents • The reality of agents • International update

3. Presenters • Professor Liz Sonenberg • University of Melbourne • Dr Andrew Lucas • Agent-Oriented Software • Dr Klaus Fischer • DFKI • Company Presenters • AOS, The Distillery, DFKI, DSTO

4. Rapid Technology Diffusion Project • Supported by DCITA under SEQC programme • Provide Australian Software Industry with access to the latest technology • National Roadshow • Develop a model for technology diffusion (Under development, not addressed here) • Consultant visits for agent assessments

5. Agents in a Nutshell • An agent is a software program that operates autonomously in a (distributed) environment sensing events and interacting with other agents to perform its goals • New in its emphasis on environment and autonomy, consolidates need for communication

6. Why agents are useful • Aid to model a complex environment • Ability to perform in an open, dynamic, unpredictable environment • Ease of interfacing with legacy software • Potential for exploiting the Internet • Potential for more intelligent software

7. Agent developments • Activities in the U.S. • featured in SEA 2000 • AgentLink in Europe • Discussed later in morning

8. The excitement of agents • Virtual marketplace • Virtual enterprise • Virtual knowledge store • Virtual environments • Simulations • Robocup • Animated characters

9. Virtual Marketplace

10. Current Examples http://www.amazone.com/ Worlds First Virtual Market Place http://www.icw.com/

12. E-Commerce ... Electronic Commerce: comprises activities of selling and purchasing products and services on line. • Business-to-Business (EDI/WebEDI Transactions) • Business-to-Consumer (Online Retailer, Auctions) • Consumer-to-Consumer (Marketplace, Auctions) • Consumer-to-Business (Reverse Auctions) Electronic Business: covers all activities devoted to electronic business processes and transactions.

13. single double outcry SB outcry SB descending ascending FPSB, Vickrey Call Market English Duch CDA Classification of Classical Auction Types

14. Consumer Buying Behaviour (CBB) Comprises actions and decisions involved in buying and using goods and services on retail markets. Three stages of E-Commerce: • Stage 1 - Information • Need Identification • Product Brokering • Merchant Brokering What to buy? Who to buy from? • Stage 2 - Purchase • Negotiation & Order • Payment & Delivery What terms of transactions? • Stage 3 - Service • Product and Customer Service, • Evaluation of buying experience and vendor

15. Agents in electronic commerce • software agents in helping mediate online transactions • six primary consumer buying behavior stages and where several representative agent systems fall

16. “Tete-a-Tete helps consumers match their needs with on-line merchants' offerings via agent-mediated integrative negotiation techniques” • sales agents automate negotiation for merchants • shopping agents provide decision support to help shoppers determine the best merchant offering

17. Tete-a-Tete negotiates not only price but warranty length and options, shipping time and cost, service contract, return policy, payment options … • decision support is based upon multi-attribute utility theory (MAUT) • “T@T's MAUT mechanism provides shoppers with a real-time, utilitarian shopping experience”

18. Towards agents for trading • technology mediated, e.g. • purchaser and goods physically separated • negotiation conducted with IT support • agent mediated • www.frictionless.com • www.extempo.com • agent driven • ...

19. www.frictionless.com • sales agents automate merchant negotiation • shopping agents help shoppers • multi-attribute comparisons • price, warranty length and options, shipping time and cost, service contract, return policy, payment options … (another university startup (USA))

20. Automated on-line trading • multiple types of auctions supported (eg) • first price • second price • (eg) Trading Agent Competition • travel planning: flights, accommodation, entertainment • managing price & preferences

21. Virtual Enterprises (VE)

22. Definition of a VE • [Byrne+93] VE = temporary limited union of independent enterprises which share abilities, costs, and market chances • [Arnold+95] • co-operation of legally independent enterprises • temporary limited • product and service oriented • participants offer their core competencies • VE offers a unique identity to the outside • no institutionalisation (e.g. central office) • operative work is based on IT

23. Set-up and Management of a VE • Set-up of a Virtual Enterprise • Product or service specification • Specification of the business process • Allocation of sub-processes to partners • Synthesis of overall process • Management of a Virtual Enterprise • Marketing • Supply Chain Management • Accounting

24. Set-up of a VE

25. Resource Allocation in a VE Factory scheduling market for resource allocation

26. P U L L P U S H Legend: = Material and Information Flow Legend: = Information Flow Supply Chain Management (SCM) Co-ordination of material and information flow in a network of suppliers, producers, distribution centres and retailers in which raw material is acquired, transformed into products and delivered to customers. (M. S. Fox, 94)

27. Architecture of an Electronic Market for VE

28. Why agents are particularly useful • Potential for exploiting the Internet • Ease of interfacing with legacy software • Aid to model a complex environment • Ability to perform in an open, dynamic, unpredictable environment • Potential for more intelligent software

29. The Virtual Knowledge Space • Information agents • Towards knowledge management • Autonomy, Verity • Examples • Gossip • AiA • Personal Picture Finder • Justice

30. What is an information agent? • Finding information from Internet • Automate searching task • Must cope with diversity • Beyond search engines • integration • presentation

31. Not agent-based! • www.google.com • “stickiness”? • e.g. MentalPlexTM search

32. www.autonomy.com • “automates the operations needed to find `gold’ in unstructured information” • based on pattern matching and neural net technology developed at Cambridge Univ. U.K. • “smart” identification of concepts using Bayesian inference

33. www.verity.com • AgentServermonitors business information sources across the Internet and intranet • actively monitors with advanced search tools • automatically filters • personalises information delivery “Avoid Infoglut with filtered push” • notifies users via e-mail, pager or personal Web page

34. the essence of information The Distillery: Canberra • InterQuest is a secure web-enabled Oracle database with interfaces to agent-based data input & analysis tools • SAM - Security Access Monitor • TINA - Text Input Analyzer • ROSE - Rule Oriented Selection Engine • PAM - Proactive Alert Monitor • VICI - Visualisation Control Agent • integration of local & purchased tools

35. Scenario: Terrorist ‘Renee Monei’ is mentioned in a French news article as being associated with ‘Action Directe’.Agency receives filtered news feeds on Terrorists and daily Passenger Manifest Lists from DIMA. Benefits • automated information discovery • automated import, matching and alerting • tailor to meet a wide range of needs Electronic news feed Unstructured data Passenger Manifest ListStructured data TINA ROSE Identifies people and flight details Name and organisation identified and linked to topic of Terrorism Matches the name as associated with Terrorism InterQuest VICI PAM A PAM notifiesthe user Visually analyseresults

36. Thfdshof fsdjlf dsflds fsdlf fds fdslfds f fsdlf dsfldsf sdlfjds lfds fldsf dlsf dlsf ldsf ljdsf sdkf dslfk sdlkfd slkf sdlkfds flksdj lfksdf lksdjfslkd jflkdsfljkdsfjlkdsf dsflds fdslf sdllfldf dslfds sadh o afjla lfsadj lkfsad fkjljia fsa fj;la fjp ff pfsajd pkdfjk sda fkjdsaf kjldsajflkd fsdalkf dskf Thfdshof fsdjlf dsflds fsdlf fds fdslfds f fsdlf dsfldsf sdlfjds lfds fldsf dlsf dlsf ldsf ljdsf sdkf dslfk sdlkfd slkf sdlkfds flksdj lfksdf lksdjfslkd jflkdsfljkdsfjlkdsf dsflds fdslf sdllfldf dslfds sadh o afjla lfsadj lkfs fkjljia fsa fj;la fjp ff pfsajd pkdfjk sda f TINA - Text Input Analysis Characteristics create records • Monitors internal state of designated work space for state of unstructured information. • Automatic analysis of electronic: • news feeds, RDBMS, resumes/reports, email servers, document stores, etc • Creates structure (entity) against clients defined profile. • Granularity scale. • Autonomy level • Autonomous • Semi-assist • Manual • Interacts with PAM link to document Person discover entities unstructured text Address Organisation

37. InterQuest InterQuestReport InterQuestMessage Phone, pager etc. PAM - Proactive Alert Monitor Characteristics • Monitors internal state of designated work space for state of user interest profile. • Automatic alert to : • User • TINA/ROSE • Proactive - • thesauri like • Responsive • Social • Interaction via • email, pager, GSM, Fax etc • Autonomy scale • Auto -- UD PAMInterest Profile PAM User notified of information found by PAM periodically searches InterQuest

38. Gossip: mobile info. agents • http://www.tryllian.com/index3.html • mobile agents are sent out into the Internet on the user's behalf to collect information • log off the Internet or turn off your computer, and agents will be waiting to return • information from • Search engines • Online databases • Information traded with other agents.

39. Gossip user interface • several agents • playground as home • agent backpackcontains user query • Internet “black hole”

41. AiA: Information Integration for Virtual Webpages PAN Travel Agent Andi Car Route Planner Yahoo News Server Yahoo Weather Server Gault Millau Restaurant Guide Hotel Guide

42. The Personal Picture Finder

43. Court Jurisdiction Division CtName Registry State City Country JUSTICE An agent-based enabling technology • concept-based search (Find all negligence cases where Judge Judy awarded for the plaintiff) • summarisation • statistics collection (Which judge is most likely to award for a plaintiff in a personal injury case?) • Performs well for Australian law cases

44. Internet info. access - smart search • Customisable access : more varied data formats/sources - smarter search • Customisable access, with personality increasing “intelligence” increasing “stickiness” of sites

45. Virtual environments • Simulation for manufacturing, wargames • RoboCup and RoboRescue • Animated characters

46. Flexible Manufacturing Plant Model

47. 3D Simulation Environment

48. SWARMM - tactics evaluation • AOD with AAII/dMARS • up to 32 agents • biggest agent • 1000 plans • 600 database entries • physical models • 100,000 lines of FORTRAN/C++ code • Typical run is • 80% physics, • 15% reasoning, • 5% overheads View from behind a strike aircraft, showing other aircraft performing an intercept on 2 enemy aircraft on combat air patrol

49. STOW-97/ TacAirSoar • Soar • programming environment based on if-then rules • TacAirSoar • modelled fixed wing aircraft (over 5000 rules) • 15 different types of aircraft • in STOW-97 running on 25 Pentiums • flew 722 missions over 48 hours • median mission time 3 hrs • typically 30 to 80 aircraft airborne • only 5% of missions had software problems