rzevsky agent models of large systems
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KNOWLEDGE GENESIS GROUP
Modelling Large Complex Systems Using Multi-Agent Technology
George RzevskiProfessor Emeritus, Complexity and Design, The Open University, UK
Chairman, Knowledge Genesis Group, London, UK
KNOWLEDGE GENESIS GROUP
COMPLEXITY
KNOWLEDGE GENESIS GROUP
Seven Criteria of Complexity
1. INTERDEPENDENCE – Complex systems consist of a large number of diverse interdependent components called Agents
2. AUTONOMY – Agents are partially autonomous (no central control) but subject to certain regulations and laws
3. EMERGENCE – Global behaviour emerges from Agent interaction and is therefore unpredictable
4. NON-EQUILIBRIUM – Systems operate far from equilibrium (at the edge of chaos)
5. NON-LINEARITY – Relations between Agents are nonlinear (butterfly effects, black swans)
6. SELF-ORGANIZATION – Systems self-organize in reaction to disruptive events (adaptability) or in order to improve performance (creativity)
7. CO-EVOLUTION – Complex systems co-evolve with their environments
KNOWLEDGE GENESIS GROUP
Classification of SystemsRANDOMSYSTEMS
COMPLEXSYSTEMS
SYSTEMS INEQUILIBRIUM
ALGORITHMS
& CLOCKS
Uncertainty Total uncertainty
Limited uncertainty
No uncertainty No uncertainty
Behaviour Random Emergent Planned, Designed
Programmed
Norms of behaviour
Total freedom
Limited freedom
No freedom Plan, design
Instructions
Organization
None Self-organizing
Organized Structured
Control None Self-control Centralized control
No need for control
Changes Random changes
Co-evolution Small deviationstemporary
None
Operatingpoint
None Far from equilibrium
Equilibrium None
KNOWLEDGE GENESIS GROUP
Where does Complexity Come From?
As evolution takes its course the complexity of ecology, society, economy and technology increases
It seems that complex systems are better at surviving and prospering in tough environments and therefore complexity is favoured by selection
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Stepwise Increase in Market Complexity
Agricultural Economy
Industrial Economy
Knowledge Economy
Agricultural Economy
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Emergence of Exceedingly Complex SystemsGlobal Cloud (global network) is emerging, which
connects: All computers, personal organisers, telephones, iPods,
iPads, TV sets, DVD players, modems, film projectors, video players, hi-fi decks, radios
Most livestock and physical resources on the planet (by means of RFID tags)
Most people on the planetGlobal Cloud stores: All digital content, i.e., data, documents, images, films,
videos, broadcasts, podcasts, newspapers, magazines, books, music, emails, blogs, websites
Global interaction of people over the Internet using: email, Skype, social networks, Internet galleries, Internet
clubs, business websites, eGovernment, eLearning, downloading and sharing music, exchanging photos and videos
KNOWLEDGE GENESIS GROUP
Co-Evolution of Society, Economy & Technology
Urban SocietyIndustrial Economy
Mass Production Technology
Global SocietyKnowledge Economy
Distributed Digital Technology
Rural SocietyAgricultural Economy
Elementary Toolsland
capital
knowledge/information
KEYRESOURCES
digital networks
motorways & railways
village roads
DISTRIBUTIONSTAGES SCOPE
local
regional
global
SUCCESSFACTORS
efficiency
economy ofscale
adaptability
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Evolution of English Language
Chaucer
Shakespeare
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Evolution of Science
Einstein
Prigogine
Newton
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Evolution of Computing
Monolithic algorithms
Swarms of interacting agents + ontology
KNOWLEDGE GENESIS GROUP
Modelling Complex Systems
KNOWLEDGE GENESIS GROUP
How Can We Model Complexity?
Complexity cannot be simplified Complex systems cannot be controlled Behaviour of complex systems cannot be predicted BUT Complexity can be managed
External complexity can be neutralised by building complexity into artefacts (making them adaptable)
Internal complexity (model complexity) can be tuned
KNOWLEDGE GENESIS GROUP
Models of Complex Systems must be Complex Complex systems change as we attempt to
construct their models and these changes must be incorporated in the model as they occur
In other words, models of complex systems must be adaptive and the adaptation must be autonomous (without waiting for instructions from the modeller), which is only possible if models have capabilities of self-organisation
Models must be able to co-evolve with situations that they model
Therefore we can postulate: Only complex models can be used to represent
complex systems.
KNOWLEDGE GENESIS GROUP
Technology for Modelling Complexity
The only technology capable of modelling complexity is Multi-Agent Technology
Agent-based software can be defined as Complex Adaptive Software
A typical architecture of multi-agent software includes:
• Knowledge Base (Ontology + Data)• Virtual World populated by software agents• Runtime engine• interfaces
KNOWLEDGE GENESIS GROUP
How Agent-Based Software Works?
Agents are small self-contained computational objects capable of exchanging messages among themselves
Demand Agents send messages to Resource Agents asking them to bid for demand fulfilments
Resource Agents send messages to Demand Agents with their bids
Before composing/answering a message Agents consult Enterprise Knowledge Base, where knowledge on how to conduct business is stored
KNOWLEDGE GENESIS GROUP
Agent Based Models of Complex Systems
Ontology
Conceptualknowledge
Data
Virtual WorldSoftware Agents
Modified State
Data
Factual knowledge
Current State
Complex Real SystemComplex Real System
Current state Event Next state
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Partitioning of Large Systems to Prevent Instability
Social Unit 1
Social Unit 2
Social Unit 3
Social Unit 4
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Emergent Intelligence
Intelligence is capability to solve problems under conditions of uncertainty
In multi-agent systems intelligent behaviour emerges from the knowledge-driven conversation between agents
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Examples
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Multi-Agent Models in Commercial Use: Real-time scheduler for 2,000 taxis in London
Real-time scheduler for Avis European Operation Real-time scheduler for 10% of world capacity of seagoing
tankers Real-time scheduler for cargo for the International Space
Station Real-time scheduler for road logistics operators in the UK and
Russia Real-time scheduler for one of the largest manufacturers in
Russia Real-time system for the allocation of advertisements Real-time data mining for a London insurance company Real-time risk management system for a financial service in
London Semantic search system for research organization in the USA
KNOWLEDGE GENESIS GROUP
Architecture of the LEGO World of Agents
Retail Agents
Product Agents
Order Agents
Warehouse Agents
Delivery Agents
P1
P2P3
P4
P5
P6
P7P8
Enterprise Agent
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A Family of Space Robots
robot 3
robot 4
robot 5
robot 1
robot 2
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Intelligent Geometry Compressor
Stage 1Agent
Stage 2Agent
Stage 3Agent
Stage 4 Agent
CoordinatingAgent
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Intelligent Logistics NetworkSupplier 1
store
transporter
transporter
store
storetransporter
Intelligentparcels
Intelligentparcels
Intelligentparcels
Destination 1 Destination 2
store
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Philosophy of Complexity
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Newtonian (Deterministic) Worldview The Universe was created according to a grand design
Laws of nature are independent of time and location
Uncertainty is due to our ignorance – “God does not play dice”
The role of science is to predict
Science will sooner or later discover universal laws of nature
All knowledge will be reduced to concepts and principles of physics - reductionism
Aristotle, Kant, Newton, Einstein
KNOWLEDGE GENESIS GROUP
Complexity Science Worldview The behaviour of the Universe emerges from
interaction of its components and is inherently uncertain
The Universe evolves in time Evolution is irreversible and leads to an increase in
complexity “The future is not given” and therefore long term
predictions are not possible We must be satisfied with discovering likely patterns
of behaviours (evolving predictions) The future is under perpetual construction within
constrains imposed by natural laws, social norms, etc Buddha, Maxwell, Darwin, Popper, Prigogine