Engineering Self-Organising andSelf-Aware Electronic Institutions

Jeremy Pitt

Department of Electrical & Electronic EngineeringImperial College London, UK

AWARENESS Online Lecture SeriesRecorded: Amsterdam, 22-23 September 2011

Agenda

AgendaI Problem: resource allocation in open networks and infrastructuresI Proposal: self-organising electronic institutionsI Method: sociologically-inspired computingI Formal Characterisation and Experimental ResultsI Self-aware InstitutionsI Summary and Conclusions

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Problem Specification

Resource allocation in open embedded systemsI Common Pool Resource (CPR) problem

I exogenous: resource level determined by the environment, i.e. by externalforces beyond the control of the agents (e.g. water appropriation)

I endogenous: resource level determined by the contributions of the agentsthemselves (e.g. MANET, sensor networks)

I hybrid: both exogenous and endogenous, resource level determined byexternal forces and internal contributions (e.g. smart grid)

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Informal Operation

Resource allocation occurs in timeslicesI Exogenous

I Agents demand resourcesI Agents are allocated resourcesI Agents appropriate resources

I EndogeneousI Agents contribute resourcesI Agents demand resourcesI Agents are allocated resourcesI Agents appropriate resources

I NotesI Agents can ‘mis-behave’I Physical and conventional actions

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Formal Description

Depends on the environmentI Exogenous: resource allocation problem for set of resources P

ui = ri , ifi∑

j=1

rj 6 P

= 0, otherwise

I Endogenous: linear public good game

ui =an

n∑j=1

rj + b(1− ri), where a > b andan

< b

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Proposal: Introspection

How do people do it?I Make up and write down rules to regulate/organise behaviourI Example 1: deliberative assemblies

I Robert’s Rules of Order (RONR): standard reference manual for proceduresin deliberative assemblies

I Anything goes unless someone objectsI Example 2: common-pool resource (CPR) management

I Ostrom: self-governing institutionsI An alternative to privatisation or centralisation

I Common features of both examples: role-based protocols forimplementing conventional procedures

I Self-organisation: change the rules according to other (‘fixed’,‘pre-defined’) sets of rules

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Ostrom: Governing the Commons

Definition of an InstitutionI “set of working rules that are used to determine who is eligible to

make decisions in some arena, what actions are allowed orconstrained, ... [and] contain prescriptions that forbid, permit orrequire some action or outcome”

I Implicitly includes RONRI Conventionally agreed, mutually understood, monitored and

enforced, mutable and nestedI Nesting: tripartite analysis

I operational-, collective- and constitutional-choice rulesI Decision arenas

I Requires representation of Institutionalised Power

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Ostrom: Sustainability of the Commons

Principles of enduring institutions1. Clearly defined boundaries2. Congruence between appropriation and provision rules and the

state of the prevailing local environment3. Collective choice arrangements4. Monitoring by appointed agencies5. Flexible scale of graduated sanctions6. Access to fast, cheap conflict resolution mechanisms7. Systems of systems8. No intervention by external authorities

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Method

Sociologically-inspired computingI How to build a computational model of self-organising CPR?

PreFormal‘Theory’

ObservedPhenomena

Calculus1. . .Calculusn

ComputerModel

ObservedPerformance

6

?

- -FormalCharacterisation

PrincipledOperationalisation

TheoryConstruction

SystematicExperimentation

⇐Expressive capacity

Conceptual granularity⇒Semantic formality

Computational tractability

I Apply method to Ostrom’s theory of CPR using a formal calculus

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Calculusi (1 6 i 6 n)

Dynamic Norm-Governed Multi-Agent SystemsI Norm-governed system specification

I Physical power, institutionalised power, and permissionI Obligations, and other complex normative relationsI Sanctions and penaltiesI Roles and actions (communication language)

I ProtocolsI Protocol stack: object-/meta-/meta-meta-/etc. level protocolsI Transition protocols to instigate and implement change

I Specification SpaceI Degrees of Freedom (DoF) define changeable components of a specificationI Defined a ‘space’ and a notion of distanceI Move between points, define rules about moving between points

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Analysis: CPR Institutions as NG-MAS

Ostrom institutions as dynamic specifications

ConstitutionalChoice

CollectiveChoice

OperationalChoice

Meta-Meta-LevelProtocol

Meta-LevelProtocol

Object-LevelProtocol

AppropriationProvisionMonitoringEnforcement

Policy MakingAdjudicationManagement

GovernanceFormulation

Ostrom Institutional Rules Artikis Dynamic Specification

Access ControlResource AllocationMonitoring

Role AssignmentRule SelectionDispute Resolution

?

?

?

?

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Formal Characterisation

The Event Calculus (EC)I A general purpose action language for representing events, and for

reasoning about effects of eventsI A logical semanticsI Action language:

I Events occur at specific times (when they ‘happen’)I A set of events, each with a given time, is called a narrativeI Given a start state and a narrative, can compute what holds in the end state

(and each point in between)I Implementation

I Implementation directly in Prolog (as well as in other programminglanguages)

I In Prolog, the specification is its own implementation;I Hence, executable specification

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Institutional Principles in Event Calculus

The institutional principles as EC ProtocolsI Clearly defined boundaries⇒ role-assignment and role-based

access controlI Congruence between appropriation and provision rules and the

state of the prevailing local environment⇒ mapping Bf to If byopinion formation and expressed preferences

I Collective choice arrangements⇒ voting protocol and participatoryadaptation

I Monitoring⇒ event recognitionI Flexible scale of graduated sanctions⇒ objections and sanctionsI Access to fast, cheap conflict resolution mechanisms⇒ alternative

dispute resolutionJeremy Pitt Engineering Self-Organising and Self-Aware Electronic Institutions 12 / 19

Experimental Testbed

The EC rules can be used as a specification for anexperimental testbed

I Class diagram:

Memberag_name {I}activitycompliancy_degree

request();appropriate();rev_behaviour();appeal();

Institutionresource_levelra_methodmonitoring_freqsanctioning_gradeadr_methodunintent_violation

refill();

Monitorag_name

report();

* 1

Headag_name

allocate();declare_raMeth();sanction();uphold();exclude();

0..1

1

10..1

I Agent state chart:

cactiveMember

inactiveMember

allocate

[comply !Pr 4]

[!comply Pr 4]v

v

[(|offences| <= limit Pr 5) (uphold Pr 6)]v v v

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Experiments

Experimental setupI Define agent population and profiles

I 100 agents, active member’s demand ≈ 50, varying refill ratesI 100 trials with a maximum lifespan tmax = 500I all or only 50% of the agents complyI agents get chance to change their behaviour when readmittedI no or low probability of unintentional violation

I Increasing subset of principles selectednone: agents allocate at will

2: ra method ∈ {queue, ration}, depending on P2/4: + high or low level of monitoring (permanent exclusion for first detected

offence)2/4/5: + temporary exclusion (for 5/10/15 time steps, permanently thereafter)

2/4/5/6: + dispute resolved if time between two offences > set amount of steps

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Experimental Results

Iterate over agent population with active principlesI Example: 50% non-compliant, high monitoring, unintentional

violation

I Primary observationsI Principles fit for purpose for enduring electronic institutionsI Sustainability (endurance and ‘fairness’) sensitive to congruence (trade-off

cost vs. agent profiles)Jeremy Pitt Engineering Self-Organising and Self-Aware Electronic Institutions 15 / 19

Self-Aware Institutions

Leverage experimental outcomeI Experiments suggest design-time guidelines for self-organising

institutionsI Codify the guidelines in same logical formalismI Make the guidelines available at run-time for use by the components

themselvesI One of the 5 dimensions of self-awareness

I measurement: for (self-)observation, exchange of informationI adaption: adapt behaviour/rules to optimise individual/collective performanceI invention: invent or discover new behaviour from introspectionI self-simulation: reason about ‘what if’ questions to justify choicesI systems of systems: understanding the hierarchy and interconnectedness of

systems

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Applications of Self-Awareness

Smarter InfrastructureI Interleaving environmental awareness, specification space,

executable specification of social rules, and social computationalchoice

Specification Instance (Policy)

Specification Space

Infrastructure Prosumers Social Network

Sensors

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Summary and Conclusions

SummaryI Resource allocation in open systems can be considered from the

perspective of CPR managementI The principles for enduring institutions can be given a uniform logical

axiomatisation in an Action LanguageI The axiomatisation can be used as the basis of an experimental

testbed; experiments show that the same principles are necessaryand sufficient conditions for sustainable electronic institutions

ConclusionsI Inter-disciplinary research requires a well-found methodI Foundations for developing self-aware electronic institutions

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Acknowledgements

AcknowledgementsI Joint work with Julia Schaumeier (Imperial College London) and

Alexander Artikis (NCSR, Athens)I FP Project AWARENESS FP7 257154

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