This document discusses engineering self-organizing and self-aware electronic institutions. It proposes using principles from sociological studies of common resource management to develop formal models of institutions. These models are characterized using an event calculus and implemented as an experimental testbed. Experiments show that including principles like monitoring and sanctions leads to more sustainable resource allocation. The results provide a basis for developing self-aware institutions that can measure system performance and adapt rules to optimize outcomes.
Engineering self-organising self-aware electronic institutions-by Jeremy Pitt
1. Engineering Self-Organising and
Self-Aware Electronic Institutions
Jeremy Pitt
Department of Electrical & Electronic Engineering
Imperial College London, UK
AWARENESS Online Lecture Series
Recorded: Amsterdam, 22-23 September 2011
2. Agenda
Agenda
Problem: resource allocation in open networks and infrastructures
Proposal: self-organising electronic institutions
Method: sociologically-inspired computing
Formal Characterisation and Experimental Results
Self-aware Institutions
Summary and Conclusions
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3. Problem Specification
Resource allocation in open embedded systems
Common Pool Resource (CPR) problem
exogenous: resource level determined by the environment, i.e. by external
forces beyond the control of the agents (e.g. water appropriation)
endogenous: resource level determined by the contributions of the agents
themselves (e.g. MANET, sensor networks)
hybrid: both exogenous and endogenous, resource level determined by
external forces and internal contributions (e.g. smart grid)
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4. Informal Operation
Resource allocation occurs in timeslices
Exogenous
Agents demand resources
Agents are allocated resources
Agents appropriate resources
Endogeneous
Agents contribute resources
Agents demand resources
Agents are allocated resources
Agents appropriate resources
Notes
Agents can ‘mis-behave’
Physical and conventional actions
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5. Formal Description
Depends on the environment
Exogenous: resource allocation problem for set of resources P
i
ui = ri , if rj P
j=1
= 0, otherwise
Endogenous: linear public good game
n
a a
ui = rj + b(1 − ri ), where a > b and <b
n j=1
n
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6. Proposal: Introspection
How do people do it?
Make up and write down rules to regulate/organise behaviour
Example 1: deliberative assemblies
Robert’s Rules of Order (RONR): standard reference manual for procedures
in deliberative assemblies
Anything goes unless someone objects
Example 2: common-pool resource (CPR) management
Ostrom: self-governing institutions
An alternative to privatisation or centralisation
Common features of both examples: role-based protocols for
implementing conventional procedures
Self-organisation: change the rules according to other (‘fixed’,
‘pre-defined’) sets of rules
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7. Ostrom: Governing the Commons
Definition of an Institution
“set of working rules that are used to determine who is eligible to
make decisions in some arena, what actions are allowed or
constrained, ... [and] contain prescriptions that forbid, permit or
require some action or outcome”
Implicitly includes RONR
Conventionally agreed, mutually understood, monitored and
enforced, mutable and nested
Nesting: tripartite analysis
operational-, collective- and constitutional-choice rules
Decision arenas
Requires representation of Institutionalised Power
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8. Ostrom: Sustainability of the Commons
Principles of enduring institutions
1. Clearly defined boundaries
2. Congruence between appropriation and provision rules and the
state of the prevailing local environment
3. Collective choice arrangements
4. Monitoring by appointed agencies
5. Flexible scale of graduated sanctions
6. Access to fast, cheap conflict resolution mechanisms
7. Systems of systems
8. No intervention by external authorities
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9. Method
Sociologically-inspired computing
How to build a computational model of self-organising CPR?
Formal Calculus1 Principled
PreFormal Characterisation ... Operationalisation Computer
‘Theory’ - - Model
6 Calculusn
Theory Systematic
Construction Experimentation
Expressive capacity Semantic formality
⇐
Conceptual granularity
⇒
Computational tractability ?
Observed Observed
Phenomena Performance
Apply method to Ostrom’s theory of CPR using a formal calculus
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10. Calculusi (1 i n)
Dynamic Norm-Governed Multi-Agent Systems
Norm-governed system specification
Physical power, institutionalised power, and permission
Obligations, and other complex normative relations
Sanctions and penalties
Roles and actions (communication language)
Protocols
Protocol stack: object-/meta-/meta-meta-/etc. level protocols
Transition protocols to instigate and implement change
Specification Space
Degrees of Freedom (DoF) define changeable components of a specification
Defined a ‘space’ and a notion of distance
Move between points, define rules about moving between points
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11. Analysis: CPR Institutions as NG-MAS
Ostrom institutions as dynamic specifications
Ostrom Institutional Rules Artikis Dynamic Specification
Governance Constitutional Meta-Meta-Level
Formulation Choice Protocol
Policy Making ? ? Role Assignment
Adjudication Collective Meta-Level Rule Selection
Management Choice Protocol Dispute Resolution
Appropriation ? ?
Access Control
Provision Operational Object-Level Resource Allocation
Monitoring Choice Protocol Monitoring
Enforcement
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12. Formal Characterisation
The Event Calculus (EC)
A general purpose action language for representing events, and for
reasoning about effects of events
A logical semantics
Action language:
Events occur at specific times (when they ‘happen’)
A set of events, each with a given time, is called a narrative
Given a start state and a narrative, can compute what holds in the end state
(and each point in between)
Implementation
Implementation directly in Prolog (as well as in other programming
languages)
In Prolog, the specification is its own implementation;
Hence, executable specification
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13. Institutional Principles in Event Calculus
The institutional principles as EC Protocols
Clearly defined boundaries ⇒ role-assignment and role-based
access control
Congruence between appropriation and provision rules and the
state of the prevailing local environment ⇒ mapping Bf to If by
opinion formation and expressed preferences
Collective choice arrangements ⇒ voting protocol and participatory
adaptation
Monitoring ⇒ event recognition
Flexible scale of graduated sanctions ⇒ objections and sanctions
Access to fast, cheap conflict resolution mechanisms ⇒ alternative
dispute resolution
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14. Experimental Testbed
The EC rules can be used as a specification for an
experimental testbed
Class diagram:
Head Monitor
ag_name ag_name
allocate(); report();
declare_raMeth();
0..1
sanction();
uphold(); 1
exclude();
Member 0..1 Institution
ag_name {I} 1 resource_level
activity ra_method
compliancy_degree monitoring_freq
sanctioning_grade
request(); * 1 adr_method
appropriate(); unintent_violation
rev_behaviour();
appeal(); refill();
Agent state chart:
[(|offences| <= limit Pr 5) v (uphold Pr 6)]
v v
[comply v !Pr 4]
active inactive
[!comply Pr 4]
v
Member c Member
allocate
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15. Experiments
Experimental setup
Define agent population and profiles
100 agents, active member’s demand ≈ 50, varying refill rates
100 trials with a maximum lifespan tmax = 500
all or only 50% of the agents comply
agents get chance to change their behaviour when readmitted
no or low probability of unintentional violation
Increasing subset of principles selected
none: agents allocate at will
2: ra method ∈ {queue, ration}, depending on P
2/4: + 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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16. Experimental Results
Iterate over agent population with active principles
Example: 50% non-compliant, high monitoring, unintentional
violation
Primary observations
Principles fit for purpose for enduring electronic institutions
Sustainability (endurance and ‘fairness’) sensitive to congruence (trade-off
cost vs. agent profiles)
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17. Self-Aware Institutions
Leverage experimental outcome
Experiments suggest design-time guidelines for self-organising
institutions
Codify the guidelines in same logical formalism
Make the guidelines available at run-time for use by the components
themselves
One of the 5 dimensions of self-awareness
measurement: for (self-)observation, exchange of information
adaption: adapt behaviour/rules to optimise individual/collective performance
invention: invent or discover new behaviour from introspection
self-simulation: reason about ‘what if’ questions to justify choices
systems of systems: understanding the hierarchy and interconnectedness of
systems
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18. Applications of Self-Awareness
Smarter Infrastructure
Interleaving environmental awareness, specification space,
executable specification of social rules, and social computational
choice
Specification Specification Infrastructure Prosumers Social
Space Instance Network
(Policy)
Sensors
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19. Summary and Conclusions
Summary
Resource allocation in open systems can be considered from the
perspective of CPR management
The principles for enduring institutions can be given a uniform logical
axiomatisation in an Action Language
The axiomatisation can be used as the basis of an experimental
testbed; experiments show that the same principles are necessary
and sufficient conditions for sustainable electronic institutions
Conclusions
Inter-disciplinary research requires a well-found method
Foundations for developing self-aware electronic institutions
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20. Acknowledgements
Acknowledgements
Joint work with Julia Schaumeier (Imperial College London) and
Alexander Artikis (NCSR, Athens)
FP Project AWARENESS FP7 257154
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