Introduction to Complexity Science

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Introduction to Complexity Science

• Engineered Complexity

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Engineered Complexity
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Todays World

• Todays world is massively interconnected at an
  unprecedented scale.
• Globalisation
• International tourism, trade, terrorism, etc.
• Underpinned by advances in ICT
• Telecoms, internet, satellites, logistics, etc.
• further large-scale interconnection
• Digital NHS, UK Air-Traffic Control Centre,
  Worldwide University Network, SETI_at_Home
• Complexity-related problems are rife.

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The Net

• The internet is growing at a fantastic rate.

• 1 in 6 people are estimated to be online.
• This figure has doubled since early 2000
• The net comprises 180 million hosts.
• Measuring growth of a huge, decentralised system
  such as the web is difficult.
• Understanding its structure is even harder.
• How can we map, model manage the web?

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Big Science

• Genome analysis is generating massive amounts of
  data at an increasing rate.

In order to unlock the mysteries of health
disease, we will need to build new tools that
allow us to manage the huge amounts of complex
data, picture it, and model it. International
collaboration amongst scientists will be
increasingly important. New better
infrastructures are needed.
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Data Overload

• Satellites orbiting the earth and other remote
  sensors are generating millions of images.

• biodiversity, global warming, destructive
  weather patterns, desertification, etc.
• ATMs, point-of-sale machines, etc., generate
  similar amounts of consumer data.
• How can we efficiently (automatically) analyse
  this data in order to extract useful information
  from it?

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Collaborative Enterprise

• Firms increasingly collaborate in extended
  enterprises that are very difficult to manage.

• a complex and dynamic web of partners,
  customers, suppliers and markets.
• Tracking, predicting, and influencing the
  changing inter-dependencies is hard
• products, product parts, part producers,
  product consumers, product markets, etc.

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Health Systems

• The massive digital health record databases being
  built in hospitals and clinics could

• help integrate patient treatment
• fuel comparative studies
• Complex issues
• infra-structure security safety
• data protection ownership
• relevance in information retrieval

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Issues

• For complex engineered systems, the same issues
  arise repeatedly

• design, control, management
• massive quantities of data
• but poorly understood
• robustness, reliability, resilience
• agility, flexibility, usability
• dynamic, changing, evolving

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Complexity Friend or Foe?

• For most engineers, complexity/chaos is a
  property that needs to be extinguished.

• e.g., Reynolds number R?dv/?
• What is the Reynolds number for
• London Stock Exchange? McDonalds?
• If we knew, would we be able to set it?
• Complex systems may also solve problems
• swarm intelligence, the edge of chaos

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Living with Complexity

• If we are to exploit complexity in engineered
  systems, we will need a changed mindset

• strict hierarchy
• accountability
• provability
• fire-and-forget mentality
• Perhaps we are on the way
• ecosystems mindsets, life-cycles, webs

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Grand Challenges?

• in vivoin silico the virtual worm
• science for global ubiquitous computing
• memories for life managing information over a
  human lifetime
• scalable ubiquitous computing systems
• the architecture of brain and mind
• dependable systems evolution
• journeys in non-classical computation

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More Generally

• progressing post-genomic science
• epidemiological modelling in a complex dynamic
  world
• understanding the dynamics of markets, economies,
  etc., in a globalised world
• building effective digital corporate systems
• facilitating collaboration in large systems
• managing large-scale design/construction
• achieving intelligent infrastructure