Computer science and engineering nowadays appears to be challenged (and driven) by technological progress and quantitative growth. Among the technological progress challenges are advances in submicron and system-on-a-chip designs, novel communication technologies, micro-electro-mechanical systems, nano and materials sciences. The vast pervasion of global networks, the growing availability of wireless communication technologies for the wide, local and personal area, and the evolving ubiquitous use of mobile and embedded information and communication technologies are indicators for accelerated quantitative growth. We perceive a shift from the “one person with one computer ” paradigm, which is based on explicit

It is shown that the concept of a Universal Computer cannot be realized. Specifically, instances of a computable function F are exhibited that cannot be computed on any machine U that is capable of only a finite and fixed number of operations per step. This remains true even if the machine U is endowed with an infinite memory and the ability to communicate with the outside world while it is attempting to compute F. It also remains true if, in addition, U is given an indefinite amount of time to compute F. This result applies not only to idealized models of computation, such as the Turing Machine and the like, but also to all known general-purpose computers, including existing conventional computers, as well as contemplated ones such as quantum computers.

This article presents the STROBE model: both an agent representation and an agent communication model based on a social approach, that means interaction centred. This model represents how agents may realise the interactive, dynamic generation of services on the Grid. Dynamically generated services embody a new concept of service implying a collaborative creation of knowledge i.e. learning; services are constructed interactively between agents depending on a conversation. The approach consists of integrating selected features from Multi-Agent Systems and agent communication, language interpretation in applicative/functional programming and e-learning/human-learning into a unique, original and simple view that privileges interactions, yet including control. The main characteristic of STROBE agents is that they develop a language (environment + interpreter) for each of their interlocutors. The model is inscribed within a global approach, defending a shift from the classical algorithmic (control based) view to problem solving in computing to an interaction-based view of Social Informatics, where artificial as well as human agents operate by communicating as well as by computing. The paper shows how the model may not only account for the classical communicating agent approaches, but also represent a fundamental advance in modelling societies of agents in particular in Dynamic Service Generation scenarios such as those necessary today on the Web and proposed tomorrow for the Grid. Preliminary concrete experimentations illustrate the potential of the model; they are significant examples for a very wide class of computational and learning situations.

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Smart space and smart appliances, i.e. wirelessly ad-hoc networked, mobile, autonomous special purpose computing devices, providing largely invisible support and contextaware services have started to populate the real world and our daily lives. In such a world, where literally everything is connected to everything with invisible, wireless data links, we need new styles on how humans and things can interact. We have proposed a "spontaneous interaction" thought model, in which things start to interact once they reach physical proximity to each other: Explained using the metaphor of an "aura", which like a subtle invisible emanation or exhalation radiates from the center of an object into its surrounding, a "digital aura" is built on technologies like Bluetooth radio, RFID or IrDA together with an XML based profile description, such that if an object detects the proximity (e.g. radio signal strength) of another object, it starts exchanging and comparing profile data, and, upon sufficient "similarity" of the two profiles, starts to interact with that object. A "digital aura" depending on the implementation technology, is dense in the center of the object, and thins out towards its surrounding until it is no longer sensible by others. Profiles described as semi-structured data and attached to the object, can be matched by a structural and semantic analysis. Peer-to-peer concepts can then be used to implement applications on top of the digital aura model for spontaneous interaction.

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...

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Abstract. In the Cellular Automata (CA) literature, discrete lines inside (discrete) space-time diagrams are often idealized as Euclidean lines in order to analyze a dynamics or to design CA for special purposes. In this article, we present a parallel analog model of computation corresponding to this idealization: dimensionless signals are moving on a continuous space in continuous time generating Euclidean lines on (continuous) space-time diagrams. Like CA, this model is parallel, synchronous, uniform in space and time, and uses local updating. The main difference is that space and time are continuous and not discrete (i.e. R instead of Z). In this article, the model is restricted to Q in order to remain inside Turing-computation theory. We prove that our model can carry out any Turing-computation through two-counter automata simulation and provide some undecidability results.

Abstract: The contribution sketches a functional-computational 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 non-traditional computational characterization of conscious agents using the concept of hyper-computation. 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.

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.