Life-like agent-based programming
Power& tradition holding back progress Contents Overcome reactionaries
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Contents

  • Emergent agent-based programming page 1
  • Contents list
  • The software development problem: page 3
  • The problem (continued): page 4
  • Introduction to Just in time (JIT) manufacturing methodology page 5
  • Just in time (JIT) methodology improved quality and reduced waste in JIT manufacturing page 6
  • Adaptive web framework codelet testing system (Smiley) page 7
  • Programming with flexible goal based agents page 8
  • Generalized data structures page 9
  • Parallel exploration of alternatives page 10
  • Signalling cascades  page 11
  • Agent programming methodology page 12
  • Agent models page 13
  • Challenges of agent-based programming page 14
  • Emergent agent-based software architectures have the potential to model their behavior and learn from problems page 15
  • Backup slides follow page 16
  • Complex adaptive systems page 17
  • Signals and sensors page 18
  • Structurally enhanced state page 19
  • Flows: control and partitioning page 20
  • Network effects page 21
  • Network effects (continued) page 22
  • Introduction to schematic structures page 23
  • Emergent layers - phenomena -> physical -> chemical -> adaptive epiphenomena page 24
  • Agents: schematic aggregates generating action page 25
  • Emergent agents process environmental signals and their instance of the schematic plan to select actions which they perform page 26
  • Models provide agents with a schematic view of the world page 27
  • Modifications to the germ-line structures are performed by genetic operators  page 28
  • Phenotypic alignment: page 29
  • Natural selection: collecting situation specific beneficial recipes within an adaptive agent page 30
  • Sexual selection: page 31
  • Shewhart cycles: Walter Shewhart advocated the use of iterative cycles of: Planning, Doing, Checking and Acting to fix issues (PDCA) page 32
  • Strategies for success page 33
  • Strategies for success (continued) page 34



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This presentation applies complex adaptive system (CAS) agents to computer programming. 
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