GMU:BioArt WS16/Living machines (slime molds)

From Medien Wiki

Slime molds

“Slime mold is an informal name given to several kinds of unrelated eukaryotic organisms that can live freely as single cells, but aggregate together to form multicellular reproductive structures.”(Wikipedia D)

Slime molds belong to Protista, that is neither animal, nor fungi nor bacteria. They feed on microorganisms.

“When food is in short supply, many of these single-celled organisms will congregate and start moving as a single body. In this state they are sensitive to airborne chemicals and can detect food sources. They can readily change the shape and function of parts and may form stalks that produce fruiting bodies, releasing countless spores”(Wikipedia D)

It is said that slime molds can exhibit some degree of intelligence, like sacrifice or computation of the shortest paths to the nutrition source.

Dictyostelium

called often as social amoebae

  • Dictyostelium exhibit a form of intelligence
  • When separated they will pull themselves back together
  • They also exhibit self-sacrifice
  • They will gather and form a stalk and then a fruiting body
  • Those self making up the stalk will die. Those at the top will clump into a ball made of life spores" (Bonner)

https://www.youtube.com/watch?v=bkVhLJLG7ug&list=PLb14u5e_rEcSVd0ZjgEFHuggA6y7ozQQI

Physarum Polycephalum

Physarum Polycephalum and its life cycle

"Physarum polycephalum, literally the "many-headed slime", is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth."(wikipedia A) It feeds on bacteria, spores and other microbial creatures.

  • Vegetative phase: plasmodium (consists of networks of protoplasmic veins, and many nuclei)
  • sclerotium (hardened multinucleated tissue)
  • sporangia

Toshiyuki Nakagaki

Experiments with Physarum polycefalum finding the shortest way to the food source through the maze

3-5 min @ Heather Barnett: What humans can learn from semi-intelligent slime https://www.youtube.com/watch?v=2UxGrde1NDA

Projects

Theresa Schubert

bodymetries, 2013

“In bodymetries visitors can experience virtual slime mould growth on their skin. Visitors enter a semi dark room with a bar table in the center. Some wobbling blobs appear on a small sections of the surface. Visitors are invited to lay their arms onto the desk. The system ‘scans’ it by taking and analysing a picture. The slime mould algorithm starts to grow from the darkest area it can find on the skin.”(http://theresaschubert.com/arts-experiments/art/bodymetries-mapping-the-human-body-through-amorphous-intelligence)


James Whitting, Ben De Lacy Costello, Andrew Adamatzky

Sonification

Towards slime mould chemical sensor: Mapping chemical inputs onto electrical potential dynamics of Physarum Polycephalum Sensors and Actuators B: Chemical. response to BenzylAlcohol https://www.youtube.com/watch?v=byTJEYHaIIM https://soundcloud.com/lessnullvoid/physarum-sonification

Leslie Garcia and Paloma López

Machine shop

"Video made during the workshop Bio Machines cultural center in the 77 organized by the Laboratory of Digital Citizenship. Participants cultured Physarum polycephalum samples to understand their life cycle. They also modified web cameras to turn them into microscopes inexpensive (28 pesos each) and to closely observe their growth and oscillations using software written with processing." https://www.youtube.com/watch?v=4sp9Efokv4o

Physarum Machine

"Unconventional computing is an interdisciplinary of science where computer scientists, physicists, mathematicians, apply principles of information processing in natural systems to design novel computer devices and architectures" (Adamatzky 2007)

“The plasmodium functions as a parallel amorphous computer with parallel inputs and parallel outputs. Data are represented by spatial configurations of sources of nutrients. A program of computation is coded via configurations of repellents and attractants. Results of computation are presented by the configuration of the protoplasmic network and the localisation of the plasmodium.”(Adamatzky 2010)

“.. plasmodium is unique biological substrate that mimics universal storage modification machines, namely the Kolmogorov-Uspensky machine. In the plasmodium implementation of the storage modification machine data are represented by sources of nutrients and memory structure by protoplasmic tubes connecting the sources. In laboratory experiments and simulation we demonstrate how the plasmodium-based storage modification machine can be programmed.”(Adamatzky & Jones 2009)

Implementations

Computable Discrete Elements in the Turing Machine

In a 1936 paper by Turing, the concept of the machine is proposed as the simple idea of an apparatus which is able to compute discrete values – zeros and ones. In the same paper, Turing introduces a computing machine with an infinite length of tape and a tape head acting upon seven commands: a) read the tape, b) move the tape left, c) move tape right, d) write “zero” on the tape, e) write “one” on the tape, f) jump to another command, and g) halt. The idea of these commands is to show that output B could be processed having an initial state and some input A. The position of the tape head on the proposed apparatus processing the information is dependent on the information stored on the tape: If the input information is defined, so is the output. The problem in such a computational model is any numerically undefined variable which would cause the machine to stop processing information, or to "halt." The halting state or, according to Turing, the “decision problem" (Enscheidungsproblem) is the problem of digital computation being defined by numerical variables. Thus, the Turing machine is limited to computing all input information and to solving all given problems (Turing 1936).

Turing Machines: https://www.youtube.com/watch?v=gJQTFhkhwPA

Markov chain

"A Markov chain (discrete-time Markov chain or DTMC[1]), named after Andrey Markov, is a random process that undergoes transitions from one state to another on a state space. It must possess a property that is usually characterized as "memorylessness": the probability distribution of the next state depends only on the current state and not on the sequence of events that preceded it. This specific kind of "memorylessness" is called the Markov property. Markov chains have many applications as statistical models of real-world processes."(wikipedia (b))

Kolmogorov Machine

"Kolmogorov, or Kolmogorov-Uspensky, machines [Ko1, KU, US] are similar to Turing machines except that the tape can change its topology."(Gurevich) Also, as far as I understand, Kolmogorov Machine isn't described by discrete 0 and 1 values. Also its functions could be updated in real time over the recursive method. On the other hand both Turing Machine and Kolmogorov machine, could emulate each other, so at the end the difference is just in the way how the machines compute their functions.

"Мы остановимся на следующих вариантах математического опреде­ ления вычислимой функции или алгоритма: A) Определение вычислимой функции как функции, значения которой выводимы в некотором логическом исчислении (Гёдель [4], Чёрч [5]1)). Б) Определение вычислимой функции как функции, значения кото­ рой получаются при помощи исчисления Х-коиверсии Чёрча [5], [7]. B) Определение вычислимой функции как функции частично-рекур­ сивной (см. работу Клини [8])2) или —для случая всюду определенной функции —как общерекурсивной (Клини [10]). (Термины «частично-рекур­ сивная» и «общерекурсивная» понимаются здесь в смысле приложения I). Г) Вычислительная машина Тьюринга [ И ] 3 ) . Д) Финитный комбинаторный процесс Поста [13]. Е) Нормальный алгорифм А. А. Маркова [1], [2]." (Колмогоров & Успенский 1958)

"Kolmogorov machines tape similarly to Schönhage’s tape is a finite connected graph with a distinguished (active) node. They work upon partly recursive function, changing instructions in real time." (Gurevich)

"Instructions: 1. add a new node together with a pair of edges of some colors between the active node and the new one, 2. remove a node and the edges incident to it, 3. add a pair of edges of some colors between two existing nodes, 4. remove the two edges between two existing nodes, 5. halt. "(Gurevich)

"Grigoriev [Gr] exhibited a function real-time computable by some KU machine but not real-time computable by any Turing machine."(Gurevich)

References