Agents, Power and Norms

Michael Luck, Fabiola López y LópezUniversity of Southampton, UKBenemérita Universidad Autonoma de Puebla, Mexico

Part I

Michael Luck, Fabiola López y LópezUniversity of Southampton, UKBenemérita Universidad Autonoma de Puebla, Mexico

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

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.

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?

Overview

Autonomous Agents

Normative Multi-Agent Systems

Institutional Powers

Personal Powers

Conclusions

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.

Overview

Norms and Normative Agents

Normative Multi-Agent Systems

Dynamics of Norms

Norm Relationships

Conclusions

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 systems cannot exist without some interaction among their members.

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 adopted or complied with

aware of the consequences of dismissing norms.

Normative Multi-Agent Systems A normative 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.

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.

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.

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)

Dynamics of NormsIssue Spread

Adoption

Activation

Reward

Compliance

Violation

Modification

Abolition

Sanction Non-sanction

Dismissal

Legislation norms

legislators membersRelations of authority

Active norms

defenders

addressees beneficiaries

Enforcement

relations

Relations of responsibility

Relations of benefit

Fulfilled Norms

defenders

addressees beneficiaries

Entitled to give

rewards

Right to claim

rewards

Violated Norms

defenders

addressees beneficiaries

Entitled

to punish

Relations of deception

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.

Z Specification

Z Specification

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.

Part II

Michael Luck, Fabiola López y LópezUniversity of Southampton, UKBenemérita Universidad Autonoma de Puebla, Mexico

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.

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)

Normative Multi-Agent Systems

Norm Structure

Normative Goals

Addressees

Context

Exceptions

Beneficiaries

Rewards

Punishments

Normative Multi-Agent Systems

Normative multi-agent system model (RASTA’02 at AAMAS’02)

Members

System norms

Legislation norms

Enforcement norms

Reward norms

Normative Multi-Agent Systems

Legislation norms allow some agents to create, modify, and abolish the norms of the system.

Issue and abolition of norms permitted

Legislation norm

normative goals punishmentscontext rewards legislators . . .

Normative Multi-Agent Systems

Enforcement norms are norms which specify what kinds of punishments must be applied when norms are unfulfilled, and who is responsible for the punishment.

unsatisfied normative goals

Norm normative goals punishmentscontext rewards addressees . . .

Enforcement norm

normative goals punishmentscontext rewards defenders . . .

Normative Multi-Agent Systems Reward norms are norms to specify

who is responsible for rewards due to norm compliance.

satisfied normative goals

Norm normative goals punishmentscontext rewards addressees . . .

Reward norm

normative goals punishmentscontext rewards defenders . . .

Institutional Powers

Legislation norms

legislators membersLegal Power

Institutional Powers

Reward norms

defendersaddresseesLegal Reward Power

Institutional Powers

Enforcement norms

defenders addresseesLegal Coercive Power

Institutional Powers

System norms

beneficiaries addresseesLegal Benefit Power

Personal Powers

Agent capabilities to satisfy goals

Ag satisfy (g1)

benefit

s

Ag (g2)

hindersAg

(g3) Illegal Coercive Power

Ag (g3)

Ag satisfy (g1)

Facilitation Power

Ag (g2)

Ag satisfy (g1)

Personal Powers

Agent benevolence towards a group of agents

Comrade Power

Ag satisfy (g1)Ag

(g2)Facilitation

Power

Ag satisfy (g1)

comrades

Personal Powers

Agent rewarded by past actions

Facilitation Power

Ag (g2)

Ag satisfy (g1)

Reciprocation Power

Ag (g2)

Ag satisfy (g1)

Fulfilled Norm Benefits

Ag (g2) Ag satisfy (g1)

Personal Powers

Agents exchange goals

Facilitation Power

Ag (g2)

Ag satisfy (g1)

Exchange Power

Ag (g2)

Ag (g4)

Facilitation Power

Ag (g4)

Ag satisfy (g3)Exchange Power

Ag (g4)

Ag (g2)

Z Specification

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.

Part III

Michael Luck, Fabiola López y LópezUniversity of Southampton, UKBenemérita Universidad Autonoma de Puebla, Mexico

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?

Overview

Norms and Normative Agents

The Norm Compliance Process

Strategies for Norm Compliance

Experiments with Normative Agents

Conclusions and Additional Work

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.

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 adopted or complied with.

aware of the consequences of dismissing norms.

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.

Norm Compliance: norm processing

normsactive norms

intended norms

rejected norms

Norm Compliance: affected goals

normative goals

hindered by

normative gs

rewardsbenefited

fromrewards

intended norms

punishmentshindered

bypunishments

rejected norms

Norm Compliance: updating goals

currentgoals

goals normative goals

hindered by

normative gs

benefited from

rewards

hindered by

punishments

Strategies for Norm Compliance Social

All norms are complied with.

Rebellious All norms are rejected.

Fearful A norm including

punishments is always complied with.

Greedy A norm including rewards

is always complied with.

norm with punishment

norm

intendednorms

norm with reward

Analysis of active norms

active norms

hindered by

normative gs =

non-conflicting

norms

hindered by

normative gs

conflictingnorms

Pressured Strategy

Non-conflicting norms are complied with if their punishments hinder any existing goal.

intendednorms

nonconflicting

norms

=

hindered by

punishments

hindered by

normative gs

Pressured Strategy

Conflicting norms are complied with if the goals hindered by punishments are more important than the goals hindered by normative goals.

intendednorms

conflictingnorms

hindered by

normative gs

hindered by

punishments >hindered

bynormative gs

hindered by

punishments

Opportunistic Strategy

Non-conflicting norms are complied with if the offered rewards might benefit a goal.

intendednorms

nonconflicting

norms

hindered by

normative gs =

benefited from

rewards

Opportunistic Strategy

Conflicting norms are complied with if associated rewards benefit more important goals than those that might be hindered by normative goals.

intendednorms

conflictingnorms

hindered by

normative gs

benefited from

rewards

>benefited

fromrewards

hindered by

normative gs

Z Specification

Z Specification

Experiments with Normative Agents

Agent Strategies for non conflicting norms

Strategies for conflicting norms

Social Social Social

Rebellious Rebellious Rebellious

Selfish Pressured & Opportunistic

Pressured & Opportunistic

Social-SelfishSocial

Pressured & Opportunistic

Experiments with Normative Agents Individual performance is the proportion of personal

goals that become satisfied under the presence of norms.

Social contribution represents the proportion of norms complied with by an agent who has its own goals.

Experiments were run

by varying the number of conflicts between the goals of an agent and the normative goals of the corresponding norms (from 0% to 100%), and

by taking different sizes for the sets of current goals and active norms.

Experiments with Normative Agents Internal and external conditions were similar for all

agents.

Agents have similar goals

Similar norms become active at the same time.

The importance of each goal is also the same for all agents.

Complete social control was assumed.

All punishments were applied.

All offered rewards were given.

Experiments with Normative Agents

Social

0

0.2

0.4

0.6

0.8

1

1.2

0% 25% 50% 75% 100%

IP

SC

Rebellious

0

0.2

0.4

0.6

0.8

1

1.2

0% 25% 50% 75% 100%

IP

SC

Selfish

0

0.2

0.4

0.6

0.8

1

1.2

0% 25% 50% 75% 100%

IP

SC

SocialSelf

0

0.2

0.4

0.6

0.8

1

1.2

0% 25% 50% 75% 100%

IP

SC

Conclusions

A formal structure of norms that includes the different elements that must be taken into account when reasoning about norms.

A formal model to incorporate the process of norm-compliance into a BDI-like agent architecture.

A set of strategies that agents might follow to decide when norms must be complied with.

Different ways to combine strategies to define complex normative behaviours.

An analysis of normative agent behaviour when total social control is exerted.