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Challenges for Effective Open Virtual Organisations

Challenges for Effective Open Virtual Organisations. Timothy J. Norman Department of Computing Science University of Aberdeen t.j.norman@abdn.ac.uk 8th Annual International Workshop on Engineering Societies in the Agents World. Outline. Open Virtual Organisations ADEPT CONOISE/CONOISE-G

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Challenges for Effective Open Virtual Organisations

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  1. Challenges for Effective Open Virtual Organisations Timothy J. Norman Department of Computing Science University of Aberdeen t.j.norman@abdn.ac.uk 8th Annual International Workshop on Engineering Societies in the Agents World Timothy J. Norman

  2. Outline • Open Virtual Organisations • ADEPT • CONOISE/CONOISE-G • e-Institutions • Semi-Structured Processes in Open Societies • Challenge 1: machine-readable organisations • Challenge 2: recognising the inevitability of conflict • Challenge 3: machinery for resolving conflicts • Towards mixed initiative (Human-Agent) VOs • Conclusions Timothy J. Norman ESAW 2007, Athens 2 of 26 Timothy J. Norman

  3. Open Virtual Organisations • What are OVOs? • Open systems – components (agents) may come and go • Organisation – system has some degree of established structure & operation • A tension… • Suppose some agent plays a unique role in an organisation; that agent leaves! • Suppose a new agent appears offering a new service; restructure the organisation? Timothy J. Norman ESAW 2007, Athens 3 of 26 Timothy J. Norman

  4. Example 1 ADEPT Domain: business process management. N. R. Jennings, P. Faratin, T. J. Norman, P. O'Brien and B. Odgers (2000) Autonomous Agents for Business Process Management. Int. Journal of Applied Artificial Intelligence 14 (2) 145-189. ADEPT Society vs. Process society open closed process closed open Timothy J. Norman ESAW 2007, Athens 4 of 26 Timothy J. Norman

  5. Design team agency Survey Team peers Capture Customer Details Capture Customer Requirements Identify Requirements Profile Yes Portfolio Item? Identify Service peers Quantity Surveyor Yes peers Designer Agency No Credit Vetting Agency Vet Customer Goto A Customer OK? negotiation and service management subsidiary subsidiary No Analyse Requirements Final Costing Cost Network terminate peers Responsible agents No A negotiation and service management Survey and Design Network Legal Agency Legal Review Provide Quote Services Service-level agreements Legal? Yes peers Sales team Agency ADEPT Business process Organisational structure => Service descriptions (service name Vet_Customer inputs ( CCL_Customer customer_details cli man ) outputs( CCL_Decision verdict ) guard ("") body ( sequence { check_CCL ( details = service::customer_details service::verdict = limit ) } -> ( check_CCL ) ) ) • => Enactment through • SLA negotiation • Service & task execution • renegotiation Timothy J. Norman ESAW 2007, Athens 5 of 26 Timothy J. Norman

  6. ADEPT: + & - • Decentralised workflow management • Flexibility – task/service scheduling, automated SLA (re-)negotiation • Process fixed at design time: • System organisation • Services • No workflow-level operational constraints or analysis • Throughput • Service delivery times • Quality control Timothy J. Norman ESAW 2007, Athens 6 of 26 Timothy J. Norman

  7. Society vs. Process Example 2 CONOISE CONOISE-G Domain: telecom services configuration. T. J. Norman, A. Preece, S. Chalmers, N. R. Jennings, M. Luck, V. D. Dang, T. D. Nguyen, V. Deora, J. Shao, W. A. Gray and N. J. Fiddian. (2004). Agent-based formation of virtual organisations, Knowledge-Based Systems 17:103­111. Increased system flexibility/adaptation society open Increased need to manage trust (security & privacy more complex) Increased heterogeneity of system components closed ADEPT process closed open Timothy J. Norman ESAW 2007, Athens 7 of 26 Timothy J. Norman

  8. Agents may • Bid as an individual • Bid representing an existing VO • Form a VO to bid • Agents prioritise commitments: may break a prior commitment to bid CONOISE • Package required by customer • Movie subscription • News service • >50 free text messages per month • 30 free phone minutes per month • Offers received • SP1 – 10 movies pcm, hourly news • SP2 – hourly news • SP3 – 120 texts AND 30 mins • SP4 – 5 movies pcm, 30 mins • Quality of offers assessed • Best offer combination identified through reverse auction Timothy J. Norman ESAW 2007, Athens 8 of 26 Timothy J. Norman

  9. CONOISE • Open system • Agents may come and go • New services (or service packages) may be offered • Open process • VOs exist for lifetime of service • Workflows composed of chained VOs • No designed-in organisational structure • All agents are peers in competition • ADEPT-like workflow structure can emerge Timothy J. Norman ESAW 2007, Athens 9 of 26 Timothy J. Norman

  10. Society vs. Process Let’s look a bit closer at this space society • Example 3 • e-Institutions • Agents may come and go • Governed by institutional rules • Process defined by institution • A. García-Camino, J.-A. Rodríguez-Aguilar, C. Sierra, and W. Vasconcelos. (2006). Norm-Oriented Programming of Electronic Institutions. Int. Joint Conf. Autonomous Agents and Multi-Agent Systems. open closed ADEPT process closed open Timothy J. Norman ESAW 2007, Athens 10 of 26 Timothy J. Norman

  11. Closed or Open Processes? Institution engenders trust (but agents must trust institution) Agents not permitted to act outside the protocol Security and privacy of information honoured Quality control e-Institutions encapsulate common episodal processes – why require agents to coordinate these at run-time? Agents must decide who to trust Failure may affect reputation → distrust What can/should be done & how information is used must be agreed But which e-Institution offers the coordination services required? Challenge 1: Institutional rules/policies must be machine-understandable society open e-Institutions processes closed open Timothy J. Norman ESAW 2007, Athens 11 of 26 Timothy J. Norman

  12. contract ( LoC, role ( ?cust ) role ( ?sup ) role ( ?bank ) obl ( … ), per ( … ) … ) Semi-Structured Processes Machine-understandable institutions M. J. Kollingbaum & T. J. Norman (2002). Supervised Interaction, AAMAS • A language for describing contracts • Reasoning machinery to interpret and negotiate contracts • Institutional elements to “host” contract enactment society open e-Institutions process closed semi-structured open Timothy J. Norman ESAW 2007, Athens 12 of 26 Timothy J. Norman

  13. Example: eScience α • Project PI (agent α) has contract with funding body, β, such that α is: β • Obliged to report experimental results Oα:pireport_results(α, R) • Forbidden from publishing source data FX:Ypublish(D) Fα:piclaim(X) Pα:piclaim(staff_costs) Pα:piclaim(travel) • Limited to spending project funds on staff and travel costs Timothy J. Norman ESAW 2007, Athens 13 of 26 Timothy J. Norman

  14. Example: sub-contracting δ α • Suppose α needs to sub-contract a task to generate results • It has two options: γ β • Agent γ is a publicly funded organisation that performs the task for free but requires data to be published OX:Ypublish(D) OX:Ypay(fee) we also know that pay(X) A:R→A:R claim(X) • Agentδ is a private organisation that charges a fee Timothy J. Norman ESAW 2007, Athens 14 of 26 Timothy J. Norman

  15. Example: conflict γ δ • Regardless of what α does, it will violate the contract with β α Challenge 2: agents must be able to recognise conflict situations • No sub-contract β • Sub-contract to γ • OX:Ypublish(D) Oα:pireport_results(α, R) FX:Ypublish(D) Fα:piclaim(X) Pα:piclaim(staff_costs) Pα:piclaim(travel) Oα:pireport_results(α, R) FX:Ypublish(D) Fα:piclaim(X) Pα:piclaim(staff_costs) Pα:piclaim(travel) Oα:pireport_results(α, R) FX:Ypublish(D) Fα:piclaim(X) Pα:piclaim(staff_costs) Pα:piclaim(travel) • Sub-contract to δ • OX:Ypay(fee) • pay(X) A:R→A:R claim(X) Timothy J. Norman ESAW 2007, Athens 15 of 26 Timothy J. Norman

  16. Utilising Detected Conflicts • Informs agent of the implications of signing a contract (adopting the policy of an e-Institution) • Enables focussed deliberation on what to violate, and hence what sanctions may be imposed • Agents have social autonomy • Could also guide conflict resolution… Timothy J. Norman ESAW 2007, Athens 16 of 26 Timothy J. Norman

  17. Conflict detection mechanisms • NoA (Kollingbaum & Norman) • Normative Architecture • Encodes possible plans and active norms in an adapted RETE network • Efficiently identifies whether a new norm is in conflict and what with (given options for action) • FOUND! (Vasconcelos, Kollingbaum & Norman) • First-Order Unification for Norm Deliberation • Norms combined with constraints on their application and domain axioms • Also tells us how the conflict can be resolved Timothy J. Norman ESAW 2007, Athens 17 of 26 Timothy J. Norman

  18. Team A Based on carrier off coast (South) UAVs with sensors to provide on-going visual surveillance Group of helicopters within range of NGO workers Team B resources Based to the North-East on land Group of helicopters within range of NGO workers Mechanised infantry Example: NEO • Non-combatant Evacuation Operation • Reports are received of NGO workers requiring assistance • Top priority mission to evacuate NGO workers • Task allocated to Team A commander • Teams A and B are different coalition partners Timothy J. Norman ESAW 2007, Athens 18 of 26 Timothy J. Norman

  19. Example: NEO Norms • Most effective plan: deploy UAV; assess situation; deploy helis; coordinate with UAV intelligence • Team A operates under the following norms: • Commander is obliged to evacuate the NGO workers (from NEO mission policy) • Team A is forbidden from sharing UAV-obtained intelligence with other coalition partners (from coalition operations policy) • Helicopters are forbidden from flying in bad weather (from safety policy) Timothy J. Norman ESAW 2007, Athens 19 of 26 Timothy J. Norman

  20. Example: NEO Enactment • AUV is deployed • Information from flight operations: deteriorating weather conditions • Conflict: • Continuing with Heli operation from carrier would violate safety policy • Delegating Heli evacuation to team B would violate coalition operations policy in sharing UAV intelligence • Failing to continue with NEO will violate mission policy Timothy J. Norman ESAW 2007, Athens 20 of 26 Timothy J. Norman

  21. Need for Conflict Resolution • Time and safety-critical scenario • Norm violation not an option • Must resolve conflict • Automatically, or • By requesting human intervention into the decision-making Challenge 3: Agents should have machinery to suggest resolutions to or to automatically resolve conflicts Timothy J. Norman ESAW 2007, Athens 21 of 26 Timothy J. Norman

  22. Example: Conflict Resolution • FOUND! used to identify norm conflict • FOUND! offers resolution on the basis of meta-policy (or conflict resolution strategy) legis superioris • Proposal presented to Team A commander: • Curtail coalition operations policy regarding UAV intelligence sharing in this instance • Delegate Heli evacuation of NGO workers to team B • Instruct AUV intelligence group and team B Heli group to coordinate the rescue mission Timothy J. Norman ESAW 2007, Athens 22 of 26 Timothy J. Norman

  23. Human-Agent Teamwork • This example • Further demonstrates the utility of norm conflict detection and resolution • Illustrates the need to refocus on teamwork • But not agent teamwork (ala. Cohen & Levesque; Tambe; etc.), humans and agents working as a team • Agents can use these techniques to aid humans in making complex decisions • Monitoring and restricting information flows • Managing and supporting trusted virtual environments within which humans operate Timothy J. Norman ESAW 2007, Athens 23 of 26 Timothy J. Norman

  24. Summary • Open Virtual Organisations need • Models of Norms/Contracts/Policies that are machine-readable • Mechanisms to efficiently identify norm conflicts • Mechanisms to resolve conflicts, or to coherently present solutions to users Timothy J. Norman ESAW 2007, Athens 24 of 26 Timothy J. Norman

  25. Other Dimensions Increased process complexity This is where we need to go! OVOs Increased system scale e-Institutions process closed open Timothy J. Norman ESAW 2007, Athens 25 of 26 Timothy J. Norman

  26. Acknowledgements • ADEPT (1995-1998) – Nick Jennings • CONOISE/CONOISE-G (2000-2006) – Alun Preece (now Cardiff) Nir Oren (now KCL) Nick Jennings Mike Luck • NoA (2000-2003) – Martin Kollingbaum (now CMU) • FOUND! – Wamberto Vasconcelos (Aberdeen) • ITA (International Technology Alliance) (2006-2016) – Wamberto Vasconcelos, Derek Sleeman, Katia Sycara (CMU), Simon Parsons (CUNY) • ALIVE (FP7) – from 2008 Timothy J. Norman ESAW 2007, Athens 26 of 26 Timothy J. Norman

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