Agents, Power and Norms

1. Agents, Power and Norms Michael Luck, Fabiola López y López University of Southampton, UK Benemérita Universidad Autonoma de Puebla, Mexico

2. Part I Michael Luck, Fabiola López y López University of Southampton, UK Benemérita Universidad Autonoma de Puebla, Mexico

3. Research Motivations • Agents have limited capabilities • The capabilities of others are needed to succeed • Agents are autonomous • Benevolence cannot be taken for granted • Power can be used to influence agents • Powers are neither eternal nor absolute

4. Research Motivations • Agents and Societies • Societies achieve social order through norms. • Agents must have a model of societies. • Agents must be able to recognise normative relationships. • Norms are dynamic concepts. • Agents must be aware of the changes due to norms.

5. Research Motivations • Societies and Autonomous Agents. • How can autonomous agents be integrated into societies regulated by norms? • What does an agent need to deal with norms? • What does an agent evaluate before dismissing a norm? • How are the goals of an agent affected by social regulations?

6. Overview • Autonomous Agents • Normative Multi-Agent Systems • Institutional Powers • Personal Powers • Conclusions

7. Aims • General: • To build a framework to represent agents able to exist in a society in which social order is achieved through norms. • Particular: • To provide a basic representation of norm-based systems. • To analyse the dynamics of norms. • To describe different kinds of normative relationships that agents might use in decision-making processes. • To identify powers in a society. • To identify personal powers of agents.

8. Overview • Norms and Normative Agents • Normative Multi-Agent Systems • Dynamics of Norms • Norm Relationships • Conclusions

9. Multi-Agent Systems • Formal model based on Luck and d’Inverno’s SMART agent framework. • Autonomous agents are essentially defined in terms of their capabilities, goals, beliefs and motivations. • Multi-agent systems are collections of agents from which at least one is autonomous. • Multi-agent systemscannot exist without some interaction among their members.

10. Normative Agents • A normative agent is an autonomous agent whose behaviour is 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 either adoptedor complied with • aware of the consequences of dismissing norms.

11. Normative Multi-Agent Systems • 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. • 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 other norms, and • norms to legislate.

12. Normative Systems: Membership • Autonomous agents join societies as a way to satisfy goals whose success relies on the actions of other agents. • Members recognise themselves as part of the society by adopting some of its norms. • Agents can be part of more than one society. • Compliance with norms is never taken for granted. • Enforcement and encouragement of norms are needed. • Addressees of norms must be members of the system.

13. Normative Multi-Agent Systems • Disorder and conflicts of interest might appear • when norms must be changed, and • when punishments and rewards must be applied. • These faculties are restricted to specific sets of agents through special sets of norms. • These norms specify how some agents have to behave when • norms must be changed, or • norm becomes either fulfilled or unfulfilled. • Fulfilment of norms is achieved when the corresponding normative goals become satisfied.

14. Normative Roles • From the different kinds of norms in a system, normative roles for agents can be identified. • Legislators (addressees of legislation norms) • Defenders (addressees of either enforcement or reward norms)

15. Spread Modification Adoption Abolition Activation Compliance Violation Dismissal Reward Sanction Non-sanction Dynamics of Norms Issue

16. Relations of authority Legislation norms legislators members

17. Relations of responsibility Relations of benefit Enforcement relations Active norms addressees beneficiaries defenders

18. Right to claim rewards Entitled to give rewards Fulfilled Norms addressees beneficiaries defenders

19. Relations of deception Entitled to punish Violated Norms addressees beneficiaries defenders

20. Norm Relationships • Norm relationships can be used by agents to: • To determine empowered situations of agents. • To find reasons to adopt and comply with norms. • To find reasons to provide help. • To take advantage of social benefits in order to satisfy their goals.

21. Z Specification

22. Z Specification

23. Conclusions This work gives the means for agents to reason about norms by providing: • A formal structure of norms that includes the different elements that must be taken into account when reasoning about norms. • A formal basic representation of norm-based systems. • An analysis and formalisations of the basic kinds of norms that norm-based systems have. • An analysis of the dynamics of norms. • The set of normative relationships that might emerge by adopting, complying and dismissing norms.

24. Part II Michael Luck, Fabiola López y López University of Southampton, UK Benemérita Universidad Autonoma de Puebla, Mexico

25. Autonomous Agents • Formal model based on Luck and d’Inverno’s SMART agent framework. • Autonomous agents are essentially defined in terms of their capabilities, goals, beliefs and motivations. • Interaction among agents results from one agent satisfying the goals of another.

26. Normative Multi-Agent Systems • Norms are mechanisms that a society has in order to influence the behaviour of agents. • Categories of Norms: • Obligations Prohibitions • Social Commitments Social Codes • A normative agent is an autonomous agent whose behaviour is shaped by the norms it must comply with (AAMAS’02)

27. Normative Multi-Agent Systems • Norm Structure • Normative Goals • Addressees • Context • Exceptions • Beneficiaries • Rewards • Punishments

28. Normative Multi-Agent Systems • Normative multi-agent system model (RASTA’02 at AAMAS’02) • Members • System norms • Legislation norms • Enforcement norms • Reward norms

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

30. normative goals context punishments rewards addressees . . . Norm unsatisfied normative goals Enforcement norm normative goals context punishments rewards defenders . . . Normative Multi-Agent Systems • Enforcement normsare norms which specify what kinds of punishments must be applied when norms are unfulfilled, and who is responsible for the punishment.

31. normative goals context punishments rewards addressees . . . Norm satisfied normative goals Reward norm normative goals context punishments rewards defenders . . . Normative Multi-Agent Systems • Reward normsare norms to specify who is responsible for rewards due to norm compliance.

32. Legal Power Institutional Powers • Legislation norms legislators members

33. Legal Reward Power Institutional Powers • Reward norms addressees defenders

34. Legal Coercive Power Institutional Powers • Enforcement norms defenders addressees

35. Legal Benefit Power Institutional Powers • System norms beneficiaries addressees

36. benefits Ag satisfy (g1) Ag (g2) Ag (g2) Facilitation Power Ag satisfy (g1) hinders Ag satisfy (g1) Ag (g3) Ag (g3) Illegal Coercive Power Personal Powers • Agent capabilities to satisfy goals

37. comrades Ag satisfy (g1) Ag (g2) Comrade Power Ag satisfy (g1) Facilitation Power Personal Powers • Agent benevolence towards a group of agents

38. Ag satisfy (g1) Ag (g2) Facilitation Power Ag (g2) Ag satisfy (g1) Reciprocation Power Ag (g2) Ag satisfy (g1) Fulfilled Norm Benefits Personal Powers • Agent rewarded by past actions

39. Ag satisfy (g1) Ag (g2) Facilitation Power Ag (g2) Ag (g4) Ag (g4) Ag (g2) Exchange Power Exchange Power Ag satisfy (g3) Ag (g4) Facilitation Power Personal Powers • Agents exchange goals

40. Z Specification

41. Conclusions • This work gives the means for agents to identify power in their current situations of powers in which they are. • Uses a formal model of systems regulated by norms. • Analyses powers due to the role agents play in a society. • Analyses powers due to an agent’s capabilities. • Provides a taxonomy of powers.

42. Part III Michael Luck, Fabiola López y López University of Southampton, UK Benemérita Universidad Autonoma de Puebla, Mexico

43. Research Motivations • Societies and Autonomous Agents. • How can autonomous agents be integrated into societies regulated by norms? • What does an agent need to deal with norms? • What does an agent evaluate before dismissing a norm? • How are the goals of an agent affected by social regulations?

44. Overview • Norms and Normative Agents • The Norm Compliance Process • Strategies for Norm Compliance • Experiments with Normative Agents • Conclusions and Additional Work

45. Norms and Normative Agents • Norm adoption is the process through which an agent decides to create an internal representation of a norm. • Norm compliance is the process through which an agent’s goals are updated according to the norms it has decided to comply with.

46. Norms and Normative Agents • A normative agent is an autonomous agent whose behaviour is 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 either adoptedor complied with. • aware of the consequences of dismissing norms.

47. Norms and Normative Agents • Compliance with norms is • enforced through punishments, and • encouraged through rewards. • Neither punishments nor rewards are effective without being related to the current goals of an agent. • Punishments must hinder important goals. • Rewards must benefit important goals.

48. active norms intended norms rejected norms Norm Compliance: norm processing norms

49. hindered by normative gs normative goals benefited from rewards rewards hindered by punishments punishments Norm Compliance: affected goals intended norms rejected norms

50. hindered by normative gs goals normative goals Norm Compliance: updating goals current goals benefited from rewards hindered by punishments