recentpopularlog in

complexity

« earlier   
Leverage Points: Places to Intervene in a System - The Donella Meadows Project
PLACES TO INTERVENE IN A SYSTEM

(in increasing order of effectiveness)

9. Constants, parameters, numbers (subsidies, taxes, standards).
8. Regulating negative feedback loops.
7. Driving positive feedback loops.
6. Material flows and nodes of material intersection.
5. Information flows.
4. The rules of the system (incentives, punishments, constraints).
3. The distribution of power over the rules of the system.
2. The goals of the system.
1. The mindset or paradigm out of which the system — its goals, power structure, rules, its culture — arises.
systems  complexity  process  reading  leverage  point  weakness  dimension  constant  measure  monitor 
yesterday by ramses0
Noyze Lab Research
David Burraston is an award winning artist/scientist working in the areas of technology and electronic music since the late 1970s. His experimental arts practice encompasses field recording, landscape-scale sound art, chaos/complexity, sound synthesis and electronic music. He performs, lectures, conducts workshops and creates art installations in Regional NSW and around the world. David also designs and builds sound synthesizers based on his theories of chaos/complexity science.
science  noise  research  complexity  synthesizer  music  sound  soundart  workshops  art  installations  artist  technology  landscape  fieldrecording 
2 days ago by derishus
boyter/scc: Sloc, Cloc and Code: scc is a very fast accurate code counter with complexity calculations and COCOMO estimates written in pure Go
Sloc, Cloc and Code: scc is a very fast accurate code counter with complexity calculations and COCOMO estimates written in pure Go
golang  code  complexity  cloc  sloc  tokei 
5 days ago by pinterb
Functional Bits: Lambda Calculus based Algorithmic Information Theory
Abstract
In the first part we introduce binary representations of both lambda calculus and combinatory logic, together with very concise interpreters that witness their simplicity. Along the way we present a simple graphical notation for lambda calculus, a new empty list representation, improved bracket abstraction, and a new fixpoint combinator. In the second part we review Algorithmic Information Theory, for which these interpreters provide a convenient vehicle. We demonstrate this with several concrete upper bounds on program-size complexity.
cs  complexity  binary  lambda  calcullus 
6 days ago by euler
Local causal states and discrete coherent structures (Rupe and Crutchfield, 2018)
"Coherent structures form spontaneously in nonlinear spatiotemporal systems and are found at all spatial scales in natural phenomena from laboratory hydrodynamic flows and chemical reactions to ocean, atmosphere, and planetary climate dynamics. Phenomenologically, they appear as key components that organize the macroscopic behaviors in such systems. Despite a century of effort, they have eluded rigorous analysis and empirical prediction, with progress being made only recently. As a step in this, we present a formal theory of coherent structures in fully discrete dynamical field theories. It builds on the notion of structure introduced by computational mechanics, generalizing it to a local spatiotemporal setting. The analysis’ main tool employs the local causal states, which are used to uncover a system’s hidden spatiotemporal symmetries and which identify coherent structures as spatially localized deviations from those symmetries. The approach is behavior-driven in the sense that it does not rely on directly analyzing spatiotemporal equations of motion, rather it considers only the spatiotemporal fields a system generates. As such, it offers an unsupervised approach to discover and describe coherent structures. We illustrate the approach by analyzing coherent structures generated by elementary cellular automata, comparing the results with an earlier, dynamic-invariant-set approach that decomposes fields into domains, particles, and particle interactions."

--- *ahem* *cough* https://arxiv.org/abs/nlin/0508001 *ahem*
to:NB  have_read  pattern_formation  complexity  prediction  stochastic_processes  spatio-temporal_statistics  cellular_automata  crutchfield.james_p.  modesty_forbids_further_comment 
7 days ago by cshalizi
A Short Guide to Hard Problems | Quanta Magazine
What’s easy for a computer to do, and what’s almost impossible? Those questions form the core of computational complexity. We present a map of the landscape.
algorithms  complexity  programming  computation 
15 days ago by gdw

Copy this bookmark:





to read