Adaptive Systems Revision Lecture

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Adaptive SystemsRevision Lecture

• Dr Giovanna Di Marzo Serugendo
• Department of Computer Science
• and Information Systems
• Birkbeck College, University of London
• Email dimarzo_at_dcs.bbk.ac.uk
• Web Page http//www.dcs.bbk.ac.uk/dimarzo

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Assessment

• Exam 70 (100 Marks)
• Coursework 20 (100 Marks)
• Presentation 10 (10 Marks)
• Exam
• June

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Overall Picture
Adaptation Mechanisms
Natural Adaptive Systems
Engineering Adaptive Systems
Model State st
Artificial Adaptive Systems
Analysis and Simulation
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Overview

• Natural Adaptive Systems
• Adaptation Mechanisms
• Artificial Adaptive Systems
• Models and Simulations
• Engineering

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Natural Adaptive Systems

• Examples of natural adaptive systems
• Non-living world
• Living world
• Social behaviour
• Self-organisation
• Self-organisation is the process enabling a
  system to change its organisation in case of
  environmental changes without explicit external
  command

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Natural Adaptive Systems

• Emergent phenomena
• A structure (pattern, property or function), not
  explicitly represented at the level of the
  individual components (lower level), and which
  appears at the level of the system (higher
  level).
• Positive / negative feedback
• Positive reinforcement of perturbation leading
  to amplification of perturbation
• Negative leads towards stabilisation by avoiding
  fluctuations caused by perturbation

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Natural Adaptive Systems

• Adaptation
• Adaptation to long-term environmental changes
• Adaptation to immediate environmental changes
• Individual components behave autonomously
• Local information (up-to-date)
• Immediate response of system
• Random fluctuations
• Adaptation expected for engineered systems

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Adaptive Mechanisms

• Stigmergy
• Schools of fishes, flocks of birds
• Autopoiesis
• Trust
• Holarchy
• Market-based

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Stigmergy

• Indirect communication among components of
  self-organising system
• Occurs through modifications brought by
  individual components to their local
  environment
• Pheromone
• Chemical volatile substance
• Ants
• Work-in-progress
• Stimulus provided by previous work
• Wasps
• Stigmergy allows coordination without central
  control

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Schools of fishes

• Direct communication among components of
  self-organising system
• Schooling and Flocking
• Wave of reaction
• Communicated progressively to all components of
  school, or flock
• Need for
• Monitoring of position and speed of neighbours
• Adaptation of own position and speed
• Mechanism (attraction and repulsion rules)
• 1. Maintain a minimum distance from other objects
  in the environment, including other
  fishes/birds.
• 2. Match velocities with neighbours.
• 3. Move toward the perceived centre of mass of
  fishes/birds in its neighbourhood.

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Models and Simulations

• Models
• Simple description of system
• Types of models mathematical definition,
  computer-based model, cellular automata, neural
  network
• Simulations
• System whose behaviour represents certain
  characteristics of the system we want to analyse
• Interest
• Understanding natural system
• Defining and predicting artificial systems
• Experimentation

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Artificial Systems

• Metaphors used
• Social insects, social human behaviour (gossip,
  trust)
• Biological systems (cells),
• Business and economics
• Holons
• Translation of metaphors into artificial system
• Artificial techniques
• Metadata

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Artificial Systems

• Static Systems
• Static Problem solving
• Dynamic Systems
• Dynamic Problem Solving
• Trust-based systems
• Intrusion detection
• P2P Protocols
• Autonomic Computing

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Engineering Overview
Engineering Adaptive Systems
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Adaptation Mechanisms

• Translation of Natural Mechanisms
• Stigmergy
• Indirect communication through the environment
• Digital pheromone
• intensity, evaporation rate
• Work-in-progress
• mapping table configurations action
• Gossiping
• Informal discussion among entities
• Local exchange of information
• Neighbours list and Ranking function
• Gossip exchange and merging of information
• Update neighbours list

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Adaptation Mechanisms

• Translation of Natural Mechanisms
• Trust
• Human trust in peers
• Trust values, calculation of risk, decision of
  actions
• Updated on basis of positive/negative evidence
• Immune System
• B cells antibodies (detection and marking)T
  cells (destruction)
• Bit strings (anomaly to detect)
• Mobile agents (B and T cells)

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Adaptive Mechanisms

• Implementation of Artificial Mechanisms
• Tags
• Markings attached to individuals (agents) and
  observable by others
• Agents change behaviour on basis of utility
  function value observed in peers (tag)
• Metadata
• Additional information (metadata) about
  functional / non-functional information /
  policies
• Middleware processes metadata and components
  adapt to policies

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Engineering

• Software Agents
• An agent is a computer system situated in some
  environment, and that is capable of autonomous
  action in this environment in order to meet its
  design objectives
• Middleware infrastructures
• Intermediary software layer
• Allow communication and coordination among agents
  (entities)
• Interest for decentralised adaptive systems
• Shared environment
• Agents coordinate their work through this
  environment
• No need for central control
• May support adaptation mechanism

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Engineering

• Methodology
• Set of practices
• training materials, educational programs,
  worksheets, diagrams
• repeatedly carried out to produce software
• ADELFE Methodology
• Issues
• Interactions
• Management of uncertainty
• Design and development
• Micro- / Macro-behaviour
• Prediction of good/bad behaviour
• Control