Prof. Marie desJardins, January 28, 2016 HONR 300/CMSC 491 Complexity Prof. Marie desJardins, January 28, 2016 Complexity 1/28/16

Course Topics Complexity 1/28/16

Reproduced from Gary Flake, The Computational Beauty of Nature, MIT Press, 1998 Complexity 1/28/16

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 Complexity 1/28/16

Sources of Complexity Complexity 1/28/16

Complexity and Agents Complexity in systems arises from interactions between individual components or agents of the system Emergence is 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 Complexity 1/28/16

Parallelism michaelmcfadyenscuba.info/ reference.findtarget.com mathaware.org Complexity 1/28/16 http://hermetic.ch/

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 Complexity 1/28/16

Recursion faqs.org wikipedia.org condostx.com wallpaperstock.net Complexity 1/28/16

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 Complexity 1/28/16

Adaptation intranet.friaryschool.net pinnycohen.com mms.nps.gov scienceray.com childrenshospital.org Complexity 1/28/16

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 Complexity 1/28/16

What Does Complexity Mean to You? What did you think you were signing up for when you registered for this class? Complexity 1/28/16

How Big is a Complex System? Powers of Ten movie (9 min): https://www.youtube.com/watch?v=0fKBhvDjuy0 Complexity 1/28/16

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. Complexity 1/28/16