Synthetic Quantum Systems

So far proposed quantum computers use fragile and environmentally sensitive natural quantum systems. Here we explore the new notion that synthetic quantum systems suitable for quantum computation may be fabricated from smart nanostructures using topological excitations of a stochastic neural-type network that can mimic natural quantum systems. These developments are a technological application of process physics which is an information theory of reality in which space and quantum phenomena are emergent, and so indicates the deep origins of quantum phenomena. Analogous complex stochastic dynamical systems have recently been proposed within neurobiology to deal with the emergent complexity of biosystems, particularly the biodynamics of higher brain function. The reasons for analogous discoveries in fundamental physics and neurobiology are discussed.Comment: 16 pages, Latex, 1 eps figure fil

Emergence of Self-Organized Symbol-Based Communication \ud in Artificial Creatures

In this paper, we describe a digital scenario where we simulated the emergence of self-organized symbol-based communication among artificial creatures inhabiting a \ud virtual world of unpredictable predatory events. In our experiment, creatures are autonomous agents that learn symbolic relations in an unsupervised manner, with no explicit feedback, and are able to engage in dynamical and autonomous communicative interactions with other creatures, even simultaneously. In order to synthesize a behavioral ecology and infer the minimum organizational constraints for the design of our creatures, \ud we examined the well-studied case of communication in vervet monkeys. Our results show that the creatures, assuming the role of sign users and learners, behave collectively as a complex adaptive system, where self-organized communicative interactions play a \ud major role in the emergence of symbol-based communication. We also strive in this paper for a careful use of the theoretical concepts involved, including the concepts of symbol and emergence, and we make use of a multi-level model for explaining the emergence of symbols in semiotic systems as a basis for the interpretation of inter-level relationships in the semiotic processes we are studying

System-of-Systems Complexity

The global availability of communication services makes it possible to interconnect independently developed systems, called constituent systems, to provide new synergistic services and more efficient economic processes. The characteristics of these new Systems-of-Systems are qualitatively different from the classic monolithic systems. In the first part of this presentation we elaborate on these differences, particularly with respect to the autonomy of the constituent systems, to dependability, continuous evolution, and emergence. In the second part we look at a SoS from the point of view of cognitive complexity. Cognitive complexity is seen as a relation between a model of an SoS and the observer. In order to understand the behavior of a large SoS we have to generate models of adequate simplicity, i.e, of a cognitive complexity that can be handled by the limited capabilities of the human mind. We will discuss the importance of properly specifying and placing the relied-upon message interfaces between the constituent systems that form an open SoS and discuss simplification strategies that help to reduce the cognitive complexity.Comment: In Proceedings AiSoS 2013, arXiv:1311.319

The Emergence of Symbol-Based Communication in a Complex System of Artificial Creatures

We present here a digital scenario to simulate the emergence of self-organized symbol-based communication among artificial creatures inhabiting a virtual world of predatory events. In order to design the environment and creatures, we seek theoretical and empirical constraints from C.S.Peirce Semiotics and an ethological case study of communication among animals. Our results show that the creatures, assuming the role of sign users and learners, behave collectively as a complex system, where self-organization of communicative interactions plays a major role in the emergence of symbol-based communication. We also strive for a careful use of the theoretical concepts involved, including the concepts of symbol, communication, and emergence, and we use a multi-level model as a basis for the interpretation of inter-level relationships in the semiotic processes we are studying

An investigation of the relation of space to society: a discussion on A. Giddens, H. Lefebvre and space syntax

This thesis is dealing with the relation of society and space as a main characteristic for elucidating the design process. More particular is based on the problem which appears both in spatial and social theories of relating entities which ‘are in different scales’. This is the relation of space, which is a local notion, to society, which is a global idea or the relation of society to the everyday life, which is also local and spatial. Thιs thesis attempts to investigate the relation of society to space through this core problem by examining three theories which seem to deal with this issue. These are the Space Syntax Theory of Hillier and Hanson, the Structuration theory of Giddens and the theory of the Production of Space of Lefebvre. The first has an architectural and urban point of view of the matter, the second a sociological and the third a politico-economic. The discussion of the three theories shows that all three grasp an interrelation between society and space although each theory sees this interrelation in a different way. For the Structuration theory space has an important role in the structuration of society, for Space Syntax a constructive role of the generic forms of society and for Lefebvre an instrumental character

Investigating biocomplexity through the agent-based paradigm.

Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex

Livelisystems: a conceptual framework integrating social, ecosystem, development and evolutionary theory

Human activity poses multiple environmental challenges for ecosystems that have intrinsic value and also support that activity. Our ability to address these challenges is constrained, inter alia, by weaknesses in cross disciplinary understandings of interactive processes of change in socio-ecological systems. This paper draws on complementary insights from social and biological sciences to propose a ‘livelisystems’ framework of multi-scale, dynamic change across social and biological systems. This describes how material, informational and relational assets, asset services and asset pathways interact in systems with embedded and emergent properties undergoing a variety of structural transformations. Related characteristics of ‘higher’ (notably human) livelisystems and change processes are identified as the greater relative importance of (a) informational, relational and extrinsic (as opposed to material and intrinsic) assets, (b) teleological (as opposed to natural) selection, and (c) innovational (as opposed to mutational) change. The framework provides valuable insights into social and environmental challenges posed by global and local change, globalization, poverty, modernization, and growth in the anthropocene. Its potential for improving inter-disciplinary and multi-scale understanding is discussed, notably by examination of human adaptation to bio-diversity and eco-system service change following the spread of Lantana camera in the Western Ghats, India