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HONR 300/CMSC 491 Complexity

HONR 300/CMSC 491 Complexity. Prof. Marie desJardins, January 28, 2016. Course Topics. Reproduced from Gary Flake, The Computational Beauty of Nature , MIT Press, 1998. Topics. 1/26-2/9: 2/11-2/25: 3/1-3/10: 3/22: 3/24-3/29: 3/31-4/17: 4/12-4/19: 4/21-4/28: 5/3-5/??:.

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HONR 300/CMSC 491 Complexity

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  1. HONR 300/CMSC 491Complexity Prof. Marie desJardins, January 28, 2016

  2. Course Topics

  3. Reproduced from Gary Flake, The Computational Beauty of Nature, MIT Press, 1998

  4. Topics • 1/26-2/9: • 2/11-2/25: • 3/1-3/10: • 3/22: • 3/24-3/29: • 3/31-4/17: • 4/12-4/19: • 4/21-4/28: • 5/3-5/??: Complexity, mathematical and algorithmic background Fractals Chaos Midterm Cellular and finite-state automata (machines) Multi-agent systems NetLogo project presentations Optimization and adaptation Presentations, additional topics if time

  5. Sources of Complexity

  6. Complexity and Agents • Complexity in systems arises from interactionsbetween individual components or agentsof the system • Emergenceis the concept that system behavior is not readily inferred from individual agent behaviors: it arises from the interactions between the agents in complex and beautiful ways • Self-similarity arises when similar patterns occur at multiple levels of abstraction or multiple parts of a system • Sources of complexity: • Parallelism • Recursion • Adaptation

  7. Parallelism michaelmcfadyenscuba.info/ reference.findtarget.com mathaware.org http://hermetic.ch/

  8. Parallelism • Parallelism: Many copies of identical or highly similar agents operating simultaneously (but potentially interacting with each other) • Examples: • Biological/biochemical systems: Fish schools, ant colonies, protein folding • Mathematical models: Cellular automata • Physical processes: Galaxy formation, planetary rings • Social/technological systems: Economic markets, social networks, structure of the Internet, RAID disk arrays

  9. Recursion faqs.org wikipedia.org condostx.com wallpaperstock.net

  10. Recursion • Recursion: a repetitive process in which a process is invoked repeatedly on successively smaller versions of the entity or problem being manipulated • Examples of recursion: • Biological processes: Tree branches, seashells, coral reefs • Mathematical models: Fractals, L-systems • Physical processes: Coastal formation, sand dunes, snowflakes, cloud formations, mountain ranges • Social systems: Micromarkets, hierarchical organizations, clan systems, governmental systems, knowledge structures

  11. Adaptation intranet.friaryschool.net pinnycohen.com mms.nps.gov scienceray.com childrenshospital.org

  12. Adaptation • Adaptation: Modification of an agent or a species (collection of agents over time, through reproduction) in response to environmental pressures (competition for resources) • Examples: • Biological systems: Evolution, drug-resistant bacteria, learning and memory, cancer • Mathematical models: Dynamic optimization, feedback models • Physical processes: Global climate change, meandering river shapes, mineral formation • Social systems: Opinion formation, market fads, competitive markets, social protocols/etiquette

  13. What Does Complexity Mean to You? • What did you think you were signing up for when you registered for this class?

  14. How Big is a Complex System? • Powers of Ten movie (9 min): https://www.youtube.com/watch?v=0fKBhvDjuy0

  15. What Next? • Reminders: • The first reading journal is due 12 hours before our next class (i.e., by 8:30 p.m. on Monday, February 1). • The “Complexity in Everyday Life” assignment is due next Thursday, February 4.

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