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Simple Is Complex
- dustingetz 7y agohttps://web.archive.org/web/20190929151534/https://avdi.codes/simple-is-complex/ https://web.archive.org/web/20190929151534/https://avdi.code...
- dustingetz 7y agoI like Rich Hickey's definitions Simple (roots: sim, plex) – one fold or braid Complex – braided or folded together Easy – near to our capabilities These are really articulate definitions that helped me as a programmer. Emergent complexity from simple systems – it seems like there might be an insight here. Avdi says we can build complex systems out of simple components. He says complex systems are hard to understand. He says it's not feasible to understand the system or predict it. So they need to be measured and observed. That's interesting. I don't know if it's true that a system built out of simple components cannot be understood. How precise is the model? How many layers deep?
- uoaei 7y agoComplexity as defined in most scientific disciplines today refers to systems which are "greater than the sum of their parts," i.e., where the behavior of the whole system cannot be predicted by looking at each component in isolation, but only can be understood by the action and interaction between components and how that evolves over time. Most systems of interest are too big to enumerate all the possible n-ary interactions between constituent parts, so we must study them by other means: probe plausible simulations, define and compute statistics from observable data, or fit models which capture plausible correlations. To complicate this further, it usually takes just one cycle or feedback loop in the network / system to introduce enough complexity that most traditional analytical mathematical tools break down. I studied complex (adaptive) systems as my Master's education and can confirm most techniques reduce to "linearize around the important bits and extrapolate from there". Examples of complex systems include: social networks (IRL and online), economies, biological systems. Machine learning is one of the most promising tools for probing these because if we can fit an appropriate model, we can hopefully capture enough of the behavior that we can reliably extrapolate to unseen data / states.
- codr7 7y agoWhat was the point again? Simple isn't Complex any more than Love is War or Dark is Light. System-wide interactions between any kind of components is about as difficult as it gets.
- tempguy9999 7y agoThe article explained what that meant about as clearly as can be. If a pinch of poetic licence troubles you, skip those parts.
- splittingTimes 7y agoSecond that. This conclusion "Simplicity leads to complexity." is just too much of a shortcut of the author's own train of thought. As you said, this sentence should read "Interaction and coupling leads to complex emergent behavior". I feel this summarizes this article better.
- bch 7y agoThere’s a Alan Kay talk[0] that might illuminate for you that leap of logic about simplicity. [0] https://youtu.be/NdSD07U5uBs https://youtu.be/NdSD07U5uBs
- ssivark 7y agoIt feels like the article ended just as it was getting warmed up towards something interesting! If any HN'ers have pointers/links to other interesting analyses of emergent complexity among simple interacting agents, I'd love to read 'em!
- carapace 7y agohttps://www.santafe.edu/ https://www.santafe.edu/ https://en.wikipedia.org/wiki/Santa_Fe_Institute https://en.wikipedia.org/wiki/Santa_Fe_Institute > The Santa Fe Institute was founded in 1984 ... > SFI's original mission was to disseminate the notion of a new interdisciplinary research area called complexity theory or simply complex systems.
- ssivark 7y agoUnfortunately a pointer to the Santa Fe institute is a little too broad to my question (which was specifically about interacting agents, and I was implicitly thinking more about physical embodied beings, somewhat in the spirit of Rodney Brooks' robots). Also, I'm keen on concrete analyses rather than vague hand-wavy pontificating. That said, the Santa Fe Institute is a great resource to be reminded of every once in a while. I'm particularly a fan of a line of research being pursued by Simon Dedeo (and others). eg: Optimal high-level descriptions of dynamical systems https://arxiv.org/abs/1409.7403 https://arxiv.org/abs/1409.7403
- carapace 7y agoSorry. I don't have any good references off the top of my head for that. You know about "BEAM" robotics? https://en.wikipedia.org/wiki/BEAM_robotics https://en.wikipedia.org/wiki/BEAM_robotics W. Grey Walter's cybernetics "turtles"? https://en.wikipedia.org/wiki/William_Grey_Walter#Robots https://en.wikipedia.org/wiki/William_Grey_Walter#Robots https://en.wikipedia.org/wiki/Turtle_(robot) https://en.wikipedia.org/wiki/Turtle_(robot)
- ssivark 7y ago
- andreskytt 7y agoOliver de Weck from MIT has done a lot of work around complexity, including deriving definitions and measures. Turns out there is an objective measure as to how many microservices is optimal. The number comes to around 2.8 connections per component if I remember correctly. Can share the math, if anybody’s interested.
- jaequery 7y agotldr; Micro-services architecture can start out simple at first, but when there are many of them, it will become complex even more so than the monolithic approach.
- kdmccormick 7y agoDon't put words in the author's mouth; nowhere do they contrast microservices with monoliths. Also, one of Avdi's main points is that a proper microservice architecture is complex, but NOT complicated. And in my personal experiece, monoliths have a tendency to be complicated.
- karmakaze 7y agoTL;DR simple mechanisms can produce complex behaviours My favourite example is the few simple rules of Go leading to possible extreme superhuman strategies.
- michannne 7y agoCouldn't really take much from this article, other than I should read that book, it sounds so interesting