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How can Nature help us compute
 SOFSEM 2006: Theory and Practice of Computer Science – 32nd Conference on Current Trends in Theory and Practice of Computer Science, Merin, Czech Republic, January 21–27
, 2006
"... Abstract. Ever since Alan Turing gave us a machine model of algorithmic computation, there have been questions about how widely it is applicable (some asked by Turing himself). Although the computer on our desk can be viewed in isolation as a Universal Turing Machine, there are many examples in natu ..."
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Abstract. Ever since Alan Turing gave us a machine model of algorithmic computation, there have been questions about how widely it is applicable (some asked by Turing himself). Although the computer on our desk can be viewed in isolation as a Universal Turing Machine, there are many examples in nature of what looks like computation, but for which there is no wellunderstood model. In many areas, we have to come to terms with emergence not being clearly algorithmic. The positive side of this is the growth of new computational paradigms based on metaphors for natural phenomena, and the devising of very informative computer simulations got from copying nature. This talk is concerned with general questions such as: • Can natural computation, in its various forms, provide us with genuinely new ways of computing? • To what extent can natural processes be captured computationally? • Is there a universal model underlying these new paradigms?
SuperTuring or NonTuring? Extending the Concept of Computation
"... “Hypercomputation ” is often defined as transcending Turing computation in the sense of computing a larger class of functions than can Turing machines. While this possibility is important and interesting, this paper argues that there are many other important senses in which we may “transcend Turing ..."
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Cited by 9 (8 self)
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“Hypercomputation ” is often defined as transcending Turing computation in the sense of computing a larger class of functions than can Turing machines. While this possibility is important and interesting, this paper argues that there are many other important senses in which we may “transcend Turing computation. ” Turing computation, like all models, exists in a frame of relevance, which underlies the assumptions on which it rests and the questions that it is suited to answer. Although appropriate in many circumstances, there are other important applications of the idea of computation for which this model is not relevant. Therefore we should supplement it with new models based on different assumptions and suited to answering different questions. In alternative frames of relevance, including natural computation and nanocomputation, the central issues include realtime response, continuity, indeterminacy, and parallelism. Once we understand computation in a broader sense, we can see new possibilities for using physical processes to achieve computational goals, which will increase in importance as we approach the limits of electronic binary logic. Key words: hypercomputation, ChurchTuring thesis, natural computation, theory of computation, model of computation, Turing computation,
Definability as hypercomputational effect
 Applied Mathematics and Computation
"... The classical simulation of physical processes using standard models of computation is fraught with problems. On the other hand, attempts at modelling realworld computation with the aim of isolating its hypercomputational content have struggled to convince. We argue that a better basic understandin ..."
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Cited by 7 (6 self)
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The classical simulation of physical processes using standard models of computation is fraught with problems. On the other hand, attempts at modelling realworld computation with the aim of isolating its hypercomputational content have struggled to convince. We argue that a better basic understanding can be achieved through computability theoretic deconstruction of those physical phenomena most resistant to classical simulation. From this we may be able to better assess whether the hypercomputational enterprise is proleptic computer science, or of mainly philosophical interest.
Emergence as a ComputabilityTheoretic Phenomenon
, 2008
"... In dealing with emergent phenomena, a common task is to identify useful descriptions of them in terms of the underlying atomic processes, and to extract enough computational content from these descriptions to enable predictions to be made. Generally, the underlying atomic processes are quite well un ..."
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Cited by 5 (2 self)
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In dealing with emergent phenomena, a common task is to identify useful descriptions of them in terms of the underlying atomic processes, and to extract enough computational content from these descriptions to enable predictions to be made. Generally, the underlying atomic processes are quite well understood, and (with important exceptions) captured by mathematics from which it is relatively easy to extract algorithmic content. A widespread view is that the difficulty in describing transitions from algorithmic activity to the emergence associated with chaotic situations is a simple case of complexity outstripping computational resources and human ingenuity. Or, on the other hand, that phenomena transcending the standard Turing model of computation, if they exist, must necessarily lie outside the domain of classical computability theory. In this talk we suggest that much of the current confusion arises from conceptual gaps and the lack of a suitably fundamental model within which to situate emergence. We examine the potential for placing emergent relations in a familiar context based on Turing’s 1939 model for interactive computation over structures described in terms of reals. The explanatory power of this model is explored, formalising informal descriptions in terms of mathematical definability and invariance, and relating a range of basic scientific puzzles to results and intractable problems in computability theory. In this talk
The Turing OMachine and the DIME Network Architecture: Injecting the Architectural Resiliency into Distributed Computing
"... Turing’s omachine discussed in his PhD thesis can perform all of the usual operations of a Turing machine and in addition, when it is in a certain internal state, can also query an oracle for an answer to a specific question that dictates its further evolution. In his thesis, Turing said 'We s ..."
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Turing’s omachine discussed in his PhD thesis can perform all of the usual operations of a Turing machine and in addition, when it is in a certain internal state, can also query an oracle for an answer to a specific question that dictates its further evolution. In his thesis, Turing said 'We shall not go any further into the nature of this oracle apart from saying that it cannot be a machine. ’ There is a host of literature discussing the role of the oracle in AI, modeling brain, computing, and hypercomputing machines. In this paper, we take a broader view of the oracle machine inspired by the genetic computing model of cellular organisms and the selforganizing fractal theory. We describe a specific software architecture implementation that circumvents the halting and undecidability problems in a process workflow computation to introduce the architectural resiliency found in cellular organisms into distributed computing machines. A DIME (Distributed Intelligent Computing Element), recently introduced as the building block of the DIME computing model, exploits the concepts from Turing’s oracle machine and extends them to implement a recursive managed distributed computing network, which can be viewed as an interconnected group of such specialized oracle machines, referred to as a DIME network. The DIME network architecture provides the architectural resiliency through autofailover; autoscaling; livemigration; and endtoend transaction security assurance in a distributed system. We demonstrate these characteristics using prototypes without the complexity introduced by hypervisors, virtual machines and other layers of adhoc management software in today’s distributed computing environments.
Track Chair’s Report
"... Abstract — We restate the objective of the first workshop on Collaboration and Cloud Computing ” in WETICE 2009; “to analyze current trends in Cloud Computing and identify longterm research themes and facilitate collaboration in future research in the field that will ultimately enable global advanc ..."
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Abstract — We restate the objective of the first workshop on Collaboration and Cloud Computing ” in WETICE 2009; “to analyze current trends in Cloud Computing and identify longterm research themes and facilitate collaboration in future research in the field that will ultimately enable global advancements in the field that are not dictated or driven by the prototypical short term profit driven motives of a particular corporate entity. ” We are glad to report that the discussions started in 2009 have directly resulted in an alternative approach to selfmanaging distributed computing systems totally different from current industry trend showing a way to eliminate the complexity of virtual machines and Hypervisors. If this approach is proven to be theoretically sound (as a paper in this conference is investigating) and extend its usefulness (demonstrated through their feasibility in the form of two proofs of concepts in the last conference) to mission critical environments, the DIME network architecture may yet prove to be an important contribution to computer science. In addition to the two papers related to the DIME computing model, there are nine other long papers and two short papers selected out of twenty two submissions discussing various aspects of clouds, grids and their management. Keywordscomponent; Cloud Computing; grid computing;
The ComputabilityTheoretic Content of Emergence
, 2011
"... In dealing with emergent phenomena, a common task is to identify useful descriptions of them in terms of the underlying atomic processes, and to extract enough computational content from these descriptions to enable predictions to be made. Generally, the underlying atomic processes are quite well un ..."
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In dealing with emergent phenomena, a common task is to identify useful descriptions of them in terms of the underlying atomic processes, and to extract enough computational content from these descriptions to enable predictions to be made. Generally, the underlying atomic processes are quite well understood, and (with important exceptions) captured by mathematics from which it is relatively easy to extract algorithmic content. A widespread view is that the difficulty in describing transitions from algorithmic activity to the emergence associated with chaotic situations is a simple case of complexity outstripping computational resources and human ingenuity. Or, on the other hand, that phenomena transcending the standard Turing model of computation, if they exist, must necessarily lie outside the domain of classical computability theory. In this article we suggest that much of the current confusion arises
Abstract Definability as hypercomputational effect q
"... The classical simulation of physical processes using standard models of computation is fraught with problems. On the other hand, attempts at modelling realworld computation with the aim of isolating its hypercomputational content have struggled to convince. We argue that a better basic understandin ..."
Abstract
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The classical simulation of physical processes using standard models of computation is fraught with problems. On the other hand, attempts at modelling realworld computation with the aim of isolating its hypercomputational content have struggled to convince. We argue that a better basic understanding can be achieved through computability theoretic deconstruction of those physical phenomena most resistant to classical simulation. From this we may be able to better assess whether the hypercomputational enterprise is proleptic computer science, or of mainly philosophical interest.