GMU:BioArt WS15/Physarum polycephalum and unconventional computing: Difference between revisions
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== Physarum Machine == | == Physarum Machine == | ||
* [https://www.youtube.com/watch?v=2UxGrde1NDA Toshiyuki Nakagaki. 3-5 min @ Heather Barnett: What humans can learn from semi-intelligent slime] | |||
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) | 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) | ||
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* [http://arxiv.org/pdf/cs/0703128.pdf Implementation of a Kolmogorov–Uspensky machine on a biological substrate. (Adamatzky 2007)] | * [http://arxiv.org/pdf/cs/0703128.pdf Implementation of a Kolmogorov–Uspensky machine on a biological substrate. (Adamatzky 2007)] | ||
* [http://arxiv.org/pdf/0901.4556v1.pdf Programmable reconfiguration of Physarum machines (Adamatzky 2009)] | * [http://arxiv.org/pdf/0901.4556v1.pdf Programmable reconfiguration of Physarum machines (Adamatzky 2009)] | ||
== Computable Discrete Elements in the Turing Machine == | === 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). | 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). | ||
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Turing Machines: https://www.youtube.com/watch?v=gJQTFhkhwPA | Turing Machines: https://www.youtube.com/watch?v=gJQTFhkhwPA | ||
== Markov chain == | === 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)) | 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 Machine === | ||
Random-access machine (RAM) is an abstract machine in the general class of register machines. (wikipedia) | Random-access machine (RAM) is an abstract machine in the general class of register machines. (wikipedia) | ||