HONR 300/CMSC 491 Complexity Prof. Marie desJardins, January 31, Class Intro 1/26/10

Course Topics Class Intro 1/26/102

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

Topics 1/26-2/9: 2/14-2/28: 3/2-3/9: 3/14: 3/16-3/30: 4/4-4/11: 4/13-4/20: 4/25-5/11: Complexity, mathematical and algorithmic background Fractals Chaos Midterm Cellular and finite-state automata (machines) Multi-agent systems Optimization and adaptation Presentations, classifier systems, additional topics Class Intro 1/26/10 4

Sources of Complexity Class Intro 1/26/105

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 Class Intro 1/26/10 6

Parallelism 7 michaelmcfadyenscuba.info/ reference.findtarget.com mathaware.org

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 Class Intro 1/26/10 8

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

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 Class Intro 1/26/10 10

Adaptation Class Intro 1/26/10 11 scienceray.com childrenshospital.org intranet.friaryschool.netpinnycohen.com mms.nps.gov

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 Class Intro 1/26/10 12

Self-Organization Class Intro 1/26/10 13

How Big is a Complex System? Powers of Ten movie: Scale of the Universe animation: Class Intro 1/26/10 14

What Next? Reminder: The “Complexity in Everyday Life” assignment is due this Wednesday, February 2. Class Intro 1/26/10 15