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A Normative Framework for Agent-Based Systems

A Normative Framework for Agent-Based Systems. Fabiola López y López Benemérita Universidad Autónoma de Puebla Facultad de Ciencias de la Computación Puebla, Pue. México fabiola.lopez@siu.buap.mx Dagstuhl-Seminar 07122 18.03.2007-23.03.2007. Research Motivations.

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A Normative Framework for Agent-Based Systems

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  1. A Normative Framework for Agent-Based Systems Fabiola López y López Benemérita Universidad Autónoma de Puebla Facultad de Ciencias de la Computación Puebla, Pue. México fabiola.lopez@siu.buap.mx Dagstuhl-Seminar 07122 18.03.2007-23.03.2007

  2. Research Motivations • To computationally represent organisations, electronic institutions, coalitions, open societies, and so on, agents that can deal with norms are needed. • Agents that always obey norms. • Agents that decide whether to comply with them. Normative Multi-Agent Systems Dagstuhl_Seminar

  3. Research Questions • What is a norm? • How can a norm be represented? • What is a NMAS? • How can a NMAS be represented? • How can normative concepts be expressed? • What is a normative agent? • How can an agent normative behaviour be described?. Normative Multi-Agent Systems Dagstuhl_Seminar

  4. Purpose • Providing a general model of norms which besides including elements needed by agents to take normative decisions, allows the representation of different types of norms that agents have to deal with. • Providing a model of multi-agent systems regulated by norms that allows agents to understand their role in a society and to delimit the authority of certain agents. • Providing a model for agents that describes their normative behaviour. Normative Multi-Agent Systems Dagstuhl_Seminar

  5. Overview • The Normative Framework • Norms • Normative Agents • Normative Multi-Agent Systems • Normative Reasoning • Conclusions Normative Multi-Agent Systems Dagstuhl_Seminar

  6. SMART Framework • Formal model based on Luck and d’Inverno’sSMARTframework. • Autonomous agents are essentially defined in terms of their capabilities, goals and motivations. • Motivationsrepresent the reasons agents have to prefer one goal over another. • Theimportanceof a set of goals is a value, that depends on an agent’s motivations, such that the greater the value the more important the goals. Normative Multi-Agent Systems Dagstuhl_Seminar

  7. The Normative Framework Normative Multi-Agent Systems Dagstuhl_Seminar

  8. Norms • Normsare mechanisms that a society has in order to influence the behaviour of agents. • They prescribe what is permitted and forbidden in the society. • Norm characteristics: • prescriptiveness, • sociality and • social pressure. Normative Multi-Agent Systems Dagstuhl_Seminar

  9. Norms • Norm structure • Normative Goals • Addressees • Context • Exceptions • Beneficiaries • Rewards • Punishments Normative Multi-Agent Systems Dagstuhl_Seminar

  10. Norms Obligations Prohibitions Social Commitments Social Codes Categories of Norms Normative Multi-Agent Systems Dagstuhl_Seminar

  11. Normative Actions • Permitted actionsare those that do not prevent the satisfaction of normative goals. • Forbidden actionsare those that hinder the normative goals. • Both concepts can be easily implemented with our norm model. Normative Multi-Agent Systems Dagstuhl_Seminar

  12. Chains of Norms • Anorm instancerepresents the internalisation of a norm. It is a copy of a norm that an agent uses as a mental attitude. • A norm is considered as fulfilledby an agent if the agent has fulfilled every one of its associated normative goals. • There are norms whose activation depends on the fulfilment of other norms. These norms can make a chain of norms. Normative Multi-Agent Systems Dagstuhl_Seminar

  13. normative goals normative goals context context punishments punishments rewards rewards . . . . . . primary norm satisfied( or unsatisfied) normative goals secondary norm Chains of Norms • Norms whose activation depends on compliance with other norms are called interlocking norms.They prescribe how agents must behave in situations in which other agents either comply or do not comply with norms. Normative Multi-Agent Systems Dagstuhl_Seminar

  14. Enforcement normsare norms which specify what kinds of punishments must be applied when norms are unfulfilled, and who is responsible for the punishment. normative goals normative goals context context punishments punishments rewards rewards . . . . . . enforced norm unsatisfied normative goals enforcement norm Enforcement Norms Normative Multi-Agent Systems Dagstuhl_Seminar

  15. Reward normsare norms to specify who is responsible for rewards due to norm compliance. normative goals normative goals context context punishments punishments rewards rewards . . . . . . rewarded norm satisfied normative goals reward norm Reward Norms Normative Multi-Agent Systems Dagstuhl_Seminar

  16. Legislation norms allow some agents to create, modify, and abolish the norms of the system. normative goals context punishments rewards . . . Legislation norm Issue and abolition of norms permitted Legislation Norms Normative Multi-Agent Systems Dagstuhl_Seminar

  17. Normative Agents • A normative agent is an autonomous agent whose behaviour is partly shaped by the norms it must comply with. • A normative agent must be • able to decide, based on its own goals and motivations, whether a norm must be first adopted and second complied with • aware of the consequences of ignoring norms. Normative Multi-Agent Systems Dagstuhl_Seminar

  18. Anormative multi-agent system is a collection of normative agents which are controlled by a set of common norms varying from obligations and social commitments, to social codes. Basically, normative multi-agent systems are characterised by the membership of some agents, the norms that members are expected to comply with, norms to enforce and encourage norms fulfilment, and norms to legislate. Normative Multi-Agent Systems Normative Multi-Agent Systems Dagstuhl_Seminar

  19. Normative Reasoning

  20. Autonomous norm decisions • Norm adoption • Norm compliance • Autonomous membership • Joining a society • Staying in a society • Authority recognition • Recognising and limit authority powers. Normative Multi-Agent Systems Dagstuhl_Seminar

  21. Autonomous norm decisions • Norm adoption • Norm compliance • Autonomous membership • Joining a society • Staying in a society • Authority recognition • Recognising and limit authority powers. Normative Multi-Agent Systems Dagstuhl_Seminar

  22. Autonomous Norm Adoption • To adopt a norm • The agent must recognise itself as an addressee of the norm. • The norm must not already be adopted. • The norm must have been issued by a recognised authority • To autonomously adopt a norm • The agent must have reasons to stay in the society Normative Multi-Agent Systems Dagstuhl_Seminar

  23. Autonomous Norm Compliance • Since • Norms in a dynamic society might change. • An agent’s goals and motivations might also change. • An agent’s willingness to comply with a norm must be reconsidered when the norm becomes active. • Autonomous norm compliance • The norm deliberation process • The norm compliance process Normative Multi-Agent Systems Dagstuhl_Seminar

  24. active norms norms intended norms rejected norms The Norm Deliberation Process • Based on its goals and motivations an agent selects the norms to be complied with and the norms to be rejected (acknowledging the consequences). Normative Multi-Agent Systems Dagstuhl_Seminar

  25. normative goals addressees context beneficiaries punishments rewards What would happen What must be done When it has to be done Normative decisions • To decide whether to comply with a norm an agent observes Normative Multi-Agent Systems Dagstuhl_Seminar

  26. Selfish normative decision Normative Multi-Agent Systems Dagstuhl_Seminar

  27. hindered by normative goals normative goals benefit from rewards rewards hindered by punishments punishments The Norm Compliance Process • An agent therefore updates its goals according to the normative decisions it has made. intended norms rejected norms Normative Multi-Agent Systems Dagstuhl_Seminar

  28. hindered by normative goals goals normative goals The Norm Compliance Process • Updating of goals current goals benefit from rewards hindered by punishments Normative Multi-Agent Systems Dagstuhl_Seminar

  29. Norm Adoption norm instances intended norms Norm Deliberation motivations Norm Compliance rejected norms SMART BDI Agent beliefs goals Normative Agent Model Normative Multi-Agent Systems Dagstuhl_Seminar

  30. norm instances BDI Agent beliefs goals Normative Agent Model Norm Adoption motivations Normative Multi-Agent Systems Dagstuhl_Seminar

  31. intended norms rejected norms BDI Agent beliefs goals Normative Agent Model Norm Adoption norm instances Norm Deliberation motivations Normative Multi-Agent Systems Dagstuhl_Seminar

  32. BDI Agent beliefs goals Normative Agent Model Norm Adoption norm instances intended norms Norm Deliberation motivations Norm Compliance rejected norms Normative Multi-Agent Systems Dagstuhl_Seminar

  33. Norm Adoption norm instances intended norms Norm Deliberation Norm Compliance rejected norms BDI Agent beliefs goals Normative Agent Model motivations Normative Multi-Agent Systems Dagstuhl_Seminar

  34. Autonomous norm decisions • Norm adoption • Norm compliance • Autonomous membership • Joining a society • Staying in a society • Authority recognition • Recognising and limit authority powers. Normative Multi-Agent Systems Dagstuhl_Seminar

  35. Autonomous membership • Joining a society • To satisfy goals that cannot be satisfied by the agent itself. • To satisfy the goals more easily. • Problem • Some norms might hinder an agent’s goals • An agent must consider its responsibilitiesin the society and the contributions it can get from the society. Normative Multi-Agent Systems Dagstuhl_Seminar

  36. normative goals normative goals normative goals addressees addressees addressees context context context beneficiaries beneficiaries beneficiaries . . . . . . . . . norms agent responsibilities Joining a Society • Responsibilities are the goals an agent must satisfy whilst it remains a society member. Normative Multi-Agent Systems Dagstuhl_Seminar

  37. normative goals normative goals normative goals addressees addressees addressees context context context beneficiaries beneficiaries beneficiaries . . . . . . . . . norms other agents agent contributions Joining a Society • Contributions are the goals from which the agent finds some benefit from norms. Normative Multi-Agent Systems Dagstuhl_Seminar

  38. The social satisfaction condition • Contributions might benefit some goals and responsibilities might hinder other goals. • To enter a society an agent must recognise that the goals that benefit from contributions must be more important than the goals hindered by its responsibilities. Normative Multi-Agent Systems Dagstuhl_Seminar

  39. Staying in a Society • Once in a society, the social satisfaction condition is not the only reason for an agent to remain there. • There are other reasons associated with the relationshipsan agent has made. Normative Multi-Agent Systems Dagstuhl_Seminar

  40. Staying in a Society • Staying for goals • social satisfaction condition • Staying by ties • to comply with norms • to reciprocate with someone • to give support • by being coerced Normative Multi-Agent Systems Dagstuhl_Seminar

  41. active norms norms intended norms normative goals addressees context beneficiaries . . . rejected norms unfulfilled agent Staying in a Society • To comply with norms Normative Multi-Agent Systems Dagstuhl_Seminar

  42. normative goals addressees context beneficiaries punishments rewards =  fulfilled agent to reciprocate agent Staying in a Society • To reciprocate with someone Normative Multi-Agent Systems Dagstuhl_Seminar

  43. normative goals addressees context beneficiaries . . . group society other agent agent Staying in a Society • To give support Normative Multi-Agent Systems Dagstuhl_Seminar

  44. Staying in a Society • By being coerced • The social satisfaction condition is violated • There is an agent with a goal that hinders an important goal of the agent being coerced. Normative Multi-Agent Systems Dagstuhl_Seminar

  45. Autonomous norm decisions • Norm adoption • Norm compliance • Autonomous membership • Joining a society • Staying in a society • Authority recognition • Recognising and limit authority powers. Normative Multi-Agent Systems Dagstuhl_Seminar

  46. Recognising Authority Powers • Enforcement and reward norms allows to know who are responsible of applying sanctions. • Legislation norms allows to know who can either issue new norms or abolish current norms Normative Multi-Agent Systems Dagstuhl_Seminar

  47. Conclusions • A model of agents that voluntarily participate in a society regulated by norms. • Agents decide whether to join a society, they find reasons to stay in a society, they autonomously decide whether to adopt a norm and also whether to comply with it. • Developed a model for autonomous normative agents by using existing models of autonomous agents (SMART framework), norms and normative multi-agent systems. • Inspired by different theories of social sciences, but our aims exceed their mere formalisation in the development of open societies regulated by norms. • Societies regulated by norms and autonomous normative agents are key to modelling open agent societies needed for emerging computing environments and applications. Normative Multi-Agent Systems Dagstuhl_Seminar

  48. Current work • Modelling hierarchical organisations • Contract and policies specifications • Distributed repository of learning objects Normative Multi-Agent Systems Dagstuhl_Seminar

  49. A Normative Framework for Agent-Based Systems Thanks! Fabiola López y López fabiola.lopez@siu.buap.mx

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