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Dialogs and Interaction Schema: Characterizing the Interaction Space of Information Systems
"... Information systems design concern modeling systems that are dynamic in nature. A dynamic system essentially has two dimensions of concern  static structure and dynamic behavior. The existence of dynamics  or interactions among parts of the system distinguish a dynamic system from a heap or coll ..."
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Information systems design concern modeling systems that are dynamic in nature. A dynamic system essentially has two dimensions of concern  static structure and dynamic behavior. The existence of dynamics  or interactions among parts of the system distinguish a dynamic system from a heap or collection of parts. Specification and management of the static aspects of an information system like the data and metadata have been fairly well addressed by existing paradigms. However an understanding of the dynamic nature of information systems is still low. Currently most paradigms model behavioral properties above an existing structural model, resulting in what may be called "entity centric" modeling. Such a kind of modeling would neglect properties that can be attributed to behavioral processes themselves, and relationships that might exist among such processes. In this paper, we address behavioral modeling by first considering system behavior to be in the form of an abstract "interaction...
Agents from functionalcomputational perspective. Acta Polytechnica Hungarica 3
, 2006
"... Abstract: The contribution sketches a functionalcomputational typological scale of agents starting form the reactive ones, and puts the family of (at least minimally) conscious agents into the proposed typology. Then it discusses the traditional computational properties of agents according their ty ..."
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Abstract: The contribution sketches a functionalcomputational typological scale of agents starting form the reactive ones, and puts the family of (at least minimally) conscious agents into the proposed typology. Then it discusses the traditional computational properties of agents according their types, and sketches a way of a rather nontraditional computational characterization of conscious agents using the concept of hypercomputation. The contribution ends with relating the sketched formal approach to agents with agents embodiment, and relates embodiment of agents with their emergence of hypercomputational power.
Toward a theory of evolutionary computation
 BIOSYSTEMS
, 2005
"... We outline a theory of evolutionary computation using a formal model of evolutionary computation  the Evolutionary Turing Machine  which is introduced as the extension of the Turing Machine model. Evolutionary Turing Machines provide a better and a more complete model for evolutionary computing ..."
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We outline a theory of evolutionary computation using a formal model of evolutionary computation  the Evolutionary Turing Machine  which is introduced as the extension of the Turing Machine model. Evolutionary Turing Machines provide a better and a more complete model for evolutionary computing than conventional Turing Machines, algorithms, and Markov chains. The convergence and convergence rate are defined and investigated in terms of this new model. The sufficient conditions needed for the completeness and optimality of evolutionary search are investigated. In particular, the notion of the total optimality as an instance of the multiobjective optimization of the Universal Evolutionary Turing Machine is introduced. This provides an automatic way to deal with the intractability of evolutionary search by optimizing the quality of solutions and search costs simultaneously. Based on a new model a very flexible classification of optimization problem hardness for the evolutionary techniques is proposed.
Lineages of Automata
, 2004
"... While in the series of previous papers we designed and studied a number of models of evolving interactive systems, in the present paper we concentrate on an indepth study of a single model that turned out to be a distinguished model of evolving interactive computing: lineages of automata. A line ..."
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While in the series of previous papers we designed and studied a number of models of evolving interactive systems, in the present paper we concentrate on an indepth study of a single model that turned out to be a distinguished model of evolving interactive computing: lineages of automata. A lineage consists of a sequence of interactive finite automata, with a mechanism of passing information from each automaton to its immediate successor. In this paper, we develop the theory of lineages. We give some means to construct new lineages out of given ones and prove several properties of translations that are realized by lineages. Lineages enable a definition of a suitable complexity measure for evolving systems. We show several complexity results, including a hierarchy result. Lineages are equivalent to interactive Turing machines with advice, but they stand out because they demonstrate the aspect of evolution explicitly.
ACCELERATING MACHINES
, 2006
"... This paper presents an overview of accelerating machines. We begin by exploring the history of the accelerating machine model and the potential power that it provides. We look at some of the problems that could be solved with an accelerating machine, and review some of the possible implementation me ..."
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This paper presents an overview of accelerating machines. We begin by exploring the history of the accelerating machine model and the potential power that it provides. We look at some of the problems that could be solved with an accelerating machine, and review some of the possible implementation methods that have been presented. Finally, we expose the limitations of accelerating machines and conclude by posing some problems for further research.
Computational Completeness of Interaction Machines and Turing Machines
"... In the paper we prove in a new and simple way that Interaction machines are more powerful than Turing machines. To do that we extend the definition of Interaction machines to multiple interactive components, where each component may perform simple computation. The emerging expressiveness is due to t ..."
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In the paper we prove in a new and simple way that Interaction machines are more powerful than Turing machines. To do that we extend the definition of Interaction machines to multiple interactive components, where each component may perform simple computation. The emerging expressiveness is due to the power of interaction and allows to accept languages not accepted by Turing machines. The main result that Interaction machines can accept arbitrary languages over a given alphabet sheds a new light to the power of interaction. Despite of that we do not claim that Interaction machines are complete. We claim that a complete theory of computer science cannot exist and especially, Turing machines or Interaction machines cannot be a complete model of computation. However complete models of computation may and should be approximated indefinitely and our contribution presents one of such attempts.
Computations with Uncertain Time Constraints: Effects on Parallelism and Universality
, 2008
"... It is known that there exist computational problems that can be solved on a parallel computer, yet are impossible to be solved sequentially. Specifically, no general purpose sequential model of computation, such as the Turing Machine or the Random Access Machine, can simulate a large family of compu ..."
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It is known that there exist computational problems that can be solved on a parallel computer, yet are impossible to be solved sequentially. Specifically, no general purpose sequential model of computation, such as the Turing Machine or the Random Access Machine, can simulate a large family of computations (for example, solutions to certain realtime problems), each of which is capable of being carried out readily by a particular parallel computer. We extend the scope of such problems to the class of problems with uncertain time constraints. The first type of time constraints refers to uncertain time requirements on the input data, that is, when and for how long are the input data available. A second type of time constraints refers to uncertain deadlines for tasks. Our main objective is to exhibit computational problems in which it is very difficult to find out (read ‘compute’) what to do and when to do it. Furthermore, problems with uncertain time constraints, as described here, prove once more that it is impossible to define a ‘universal computer’, that is, a computer able to compute all computable functions. Finally, one of the contributions of this paper is to promote the study of a topic, conspicuously absent to date from theoretical computer science, namely, the role of physical time and physical space in computation. The focus of our work is to analyze the effect of external natural phenomena on the various components of a computational process, namely, the input phase, the calculation phase (including the algorithm and the computing agents themselves), and the output phase.
Time Indeterminacy, NonUniversality in Computation, and the Demise of the ChurchTuring Thesis
, 2011
"... It is known that there exist computational problems that can be solved on a parallel computer, yet are impossible to be solved sequentially. Specifically, no general purpose sequential model of computation, such as the Turing Machine or the Random Access Machine, can simulate a large family of compu ..."
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It is known that there exist computational problems that can be solved on a parallel computer, yet are impossible to be solved sequentially. Specifically, no general purpose sequential model of computation, such as the Turing Machine or the Random Access Machine, can simulate a large family of computations (for example, solutions to certain realtime problems), each of which is capable of being carried out readily by a particular parallel computer. We extend the scope of such problems to the class of problems with uncertain time constraints. The first type of time constraints refers to uncertain time requirements on the input data, that is, when and for how long are the input data available. A second type of time constraints refers to uncertain deadlines on when outputs are to be produced. Our main objective is to exhibit computational problems in which it is very difficult to find out (read ‘compute’) what to do and when to do it. Furthermore, problems with uncertain time constraints, as described here, prove once more that it is impossible to define a ‘universal computer’, that is, a computer able to perform (through simulation or