1. E-Commerce Environments as 3D Electronic Institutions Anton Bogdanovych, University of Technology Sydney e-Markets Research Group

2. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 2 Outline MotivationMotivation Research QuestionsResearch Questions ObjectivesObjectives BackgroundBackground 3D Electronic Institutions3D Electronic Institutions LearningLearning EvolutionEvolution Conclusion and Future WorkConclusion and Future Work

3. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 3 Drawbacks in contemporary E-Commerce systems Motivation

4. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 4 Drawbacks in contemporary E-Commerce systems Poor product presentation and advertisementPoor product presentation and advertisement Information overloadInformation overload Inconsistency throughout different interfacesInconsistency throughout different interfaces Lack of Social interactionsLack of Social interactions Awareness of othersAwareness of others The needs of emotional customers are not addressed (Approximately 70% of all buying decisions are made by the shopper in the store - Progressive Grocer; 10/1/1996; Armata, Kevin )The needs of emotional customers are not addressed (Approximately 70% of all buying decisions are made by the shopper in the store - Progressive Grocer; 10/1/1996; Armata, Kevin ) Motivation

5. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 5 Research questions What technology to use for addressing the drawbacks of contemporary E-Commerce?What technology to use for addressing the drawbacks of contemporary E-Commerce? What methodology to apply?What methodology to apply? How to automate the process of creating of E-Commerce environmentsHow to automate the process of creating of E-Commerce environments How to facilitate the participation of software agents there and make them believable and intelligent?How to facilitate the participation of software agents there and make them believable and intelligent? How to permit the evolution of E-Commerce environments so that the new drawbacks can be identified and the solution to address them can be computed?How to permit the evolution of E-Commerce environments so that the new drawbacks can be identified and the solution to address them can be computed? Motivation

6. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 6 3D Electronic Institutions Motivation No methodological supportNo methodological support

7. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 7 Research Objectives Establishment of the 3D Electronic Institutions concept and applying it to the domain of E-CommerceEstablishment of the 3D Electronic Institutions concept and applying it to the domain of E-Commerce User Modeling and Learning in 3D Electronic InstitutionsUser Modeling and Learning in 3D Electronic Institutions Evolution of 3D Electronic InstitutionsEvolution of 3D Electronic Institutions Objectives

8. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 8 3D Experience in E-Commerce Virtual experience vs direct and indirect experiences Terry M. Daugherty, Vanderbilt University, USA, 2001 Background

9. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 9 3D store example Luca Chittaro, University of Udine, Italy, 2004 Background

10. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 10 Does 3D shopping make sense? Has more residents than Miami Has bigger GNP per capita than Bulgaria Norrath, The online world created by Sony Virtual worlds are one of a few online businesses that make money on the Web Edward Castronova, USA, 2003 Background

11. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 11 Project Entropia multi-user game: Virtual Island sold for 26500 USD Rights available to the purchaser of the island: - A unique castle (furniture not included) - Hunting (including native forms of wildlife) - Mining (both minerals and enmatters) - Taxation rights on hunting and mining activities on the island - Income from the sale of land lots. Five lots per month will be available for sale under the duration of one year. These 60 lots alone have an estimated market value of 300 000 PED. - Massive revenue potential Treasure Island (6000 Acres/25 km²) Does 3D shopping make sense? Background

12. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 12 3D Virtual Worlds – future trends Scanning Physical interaction behaviors of 3D objects Dinesh K. Pai, The University of British Columbia, 2005 Background

13. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 13 3D Virtual Worlds – future trends Fast automated 3D Model Reconstruction Christian Frueh, University of California at Berkeley, 2005 Background

14. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 14 Electronic Institutions Natural extension of the social concept of institutions as regulatory systems shaping human interactionsNatural extension of the social concept of institutions as regulatory systems shaping human interactions Software systems inhabited by autonomous entities = software agentsSoftware systems inhabited by autonomous entities = software agents Agents interact according to predefined conventions on language and protocolAgents interact according to predefined conventions on language and protocol Conventions guarantee that certain norms of behaviour are enforcedConventions guarantee that certain norms of behaviour are enforced Background

15. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 15 Electronic Institutions Conventions Conventions –on Language = Dialogical Framework –on Activities = Performative Structure –on Behaviour = Norms Background

16. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 16 Dialogical Framework Language (Ontology)Language (Ontology) Illocutionary ParticlesIllocutionary Particles –Theory of Speech Acts –Particles are inform, failure or request Organizational Structure of the Agent SocietyOrganizational Structure of the Agent Society RolesRoles –External Vs. Internal –Incompatibilities –Relationships Background

17. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 17 Dialogical Framework Ontology (start_double_auction: -> boolean) (offer:int*float -> boolean) (demand:int*float -> boolean) (want_to_buy:String -> boolean) (want_to_sell:String -> boolean) (close_meeting: -> boolean) (close_wait: -> boolean) Role Hierarchy Background

18. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 18 Performative Structure Defines the Dialogues in which Agents might participateDefines the Dialogues in which Agents might participate Each Activity an Agent performs is associated with a Dialogue among the group of agents involved in this ActivityEach Activity an Agent performs is associated with a Dialogue among the group of agents involved in this Activity Dialogues are referred to as ScenesDialogues are referred to as Scenes Background

19. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 19 Performative Structure Fixes the Protocol (possible dialogues) which might be enacted in each SceneFixes the Protocol (possible dialogues) which might be enacted in each Scene Defines the applicable Sub-Language of a particular SceneDefines the applicable Sub-Language of a particular Scene Minimum and Maximum number of participantsMinimum and Maximum number of participants Background

20. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 20 Performative Structure Agents transit is regulated by special scenes referred to as TransitionsAgents transit is regulated by special scenes referred to as Transitions Transitions are used to re-route agentsTransitions are used to re-route agents Agents are synchronized via different types of transitionsAgents are synchronized via different types of transitions Background

21. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 21 Performative Structure Example Background

22. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 22 Performative Structure Behind the ScenesBehind the Scenes –A Finite-State Machine (FSM) regulates the Flow of Agents within particular scenes –The FSM contains special states defining possible Enter and Exit points for agents –Arcs between states are labelled with illocutionary patterns –Uttered illocutions change the state of the FSM Background

23. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 23 FSM: Behind the Scenes Example Illocution: (W0 W1(inform (?s seller) (?t tradeMgr) offer(?qty ?price)) (?qty > 0 )) Background

24. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 24 Norms Norms impose restrictions on actions agents are allowed to perform in scenesNorms impose restrictions on actions agents are allowed to perform in scenes Agents acquire Commitments / Obligations within an Electronic Institution while talkingAgents acquire Commitments / Obligations within an Electronic Institution while talking Commitments / Obligations restrict future actions of the agentCommitments / Obligations restrict future actions of the agent Background

25. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 25 Electronic Institutions Development Environment Common Ontology and language Agent Roles Multi-agent Protocols Network of protocols Norms Background

26. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 26 3D Electronic Institutions 3DEI = 3DEI = where SP stands for Specification of the institution V stands for Visualization of the institution SP = SP = where DF stands for Dialogical Framework PS stands for Performative Structure N stands for Norms A stands for visualization related Annotations of the specification V = V = where R stands for Rooms T stands for Transition D stands for Doors IA stands for Internal Agents EA stands for External Agents VA stands for Visualization of the annotated content M stands for the map of the institution O stands for obligations of the participant towards the institution (visualized as a backpack)

27. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 27 3D Electronic Institution Architecture 3D Electronic Institutions

28. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 28 Generating 3D Electronic Institutions 3D Electronic Institutions

29. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 29 Generating 3D Electronic Institutions Two approaches: Euclidian Representation (rectangular dualization – Sara Drago, Massimo Ancona, University of Genoa, Italy)Euclidian Representation (rectangular dualization – Sara Drago, Massimo Ancona, University of Genoa, Italy) Non Euclidian (teleporting, shape grammars, Mary Lou Maher, Sydney University, Australia)Non Euclidian (teleporting, shape grammars, Mary Lou Maher, Sydney University, Australia) 3D Electronic Institutions

30. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 30 Runtime Architecture 3D Electronic Institutions

31. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 31 Runtime Architecture 3D Electronic Institutions

32. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 32 Learning - the vision Background

33. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 33 Learning – related work Aris Alissandrakis, University of Hertfordshire, UK, 2001 Carlos A. Acosta Calderon, University of Essex UK, 2005 Imitation Background Daphna Buchsbaum, MIT Cambridge, 2005

34. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 34 Learning – related work Ronan Le Hy, Montbonnot, France, 2004 Training Relevent Variables Background

35. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 35 Learning – related work Anton Bogdanovych & Mathias Bauer, German Research Center for AI (DFKI), 2004 Using trajectory to asses: Cognitive loadCognitive load Future behaviourFuture behaviour Significant locationsSignificant locations Background

36. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 36 Learning – what to learn? Position + time = trajectory, velocityPosition + time = trajectory, velocity Eye direction, head rotation = visible itemsEye direction, head rotation = visible items CollisionsCollisions Positions of the othersPositions of the others GesturesGestures ActionsActions TextText Distance to objectsDistance to objects Learning

37. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 37 Whom to train? Learning

38. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 38 Learning – proposed approach Learning Social and Institutional Levels

39. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 39 Learning Learning – proposed approach

40. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 40 Evolution of 3D Electronic Institutions Evolution is the implication of learningEvolution is the implication of learning Based on observing the behavior of participants to understand how the institution should be changed to make the interactions inside more efficientBased on observing the behavior of participants to understand how the institution should be changed to make the interactions inside more efficient Includes changes in the visualization as well as changes in the specificationIncludes changes in the visualization as well as changes in the specification May happen automaticallyMay happen automatically Evolution

41. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 41 Evolution of 3D Electronic Institutions Luca Chittaro, University of Udine, Italy, 2004 Evolution

42. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 42 Conclusion 3D Electronic Institutions: Are based on Electronic Institutions and Virtual WorldsAre based on Electronic Institutions and Virtual Worlds Provide immersive environment for E-CommerceProvide immersive environment for E-Commerce Bring humans into Electronic InstitutionsBring humans into Electronic Institutions Are social and secure at the same timeAre social and secure at the same time Can be semi-automatically generated from the Electronic Institution specificationCan be semi-automatically generated from the Electronic Institution specification Provide facilities for learningProvide facilities for learning Evolution is possibleEvolution is possible Conclusion

43. Anton Bogdanovych, University of Technology Sydney E-Commerce Environments as 3D Electronic Institutions 43 Next Steps Automatic Generation of 3D Electronic InstitutionsAutomatic Generation of 3D Electronic Institutions Conduct a Field TrialConduct a Field Trial –test acceptance, usability, performance Learning – implementation & validationLearning – implementation & validation EvolutionEvolution Future Work