Nature as a Network of Morphological Infocomputational Processes for Cognitive Agents

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted

A Combined Geometric Approach for Computational Fluid Dynamics on Dynamic Grids

A combined geometric approach for computational fluid dynamics is presented for the analysis of unsteady flow about mechanisms in which its components are in moderate relative motion. For a CFD analysis, the total dynamics problem involves the dynamics of the aspects of geometry modeling, grid generation, and flow modeling. The interrelationships between these three aspects allow for a more natural formulation of the problem and the sharing of information which can be advantageous to the computation of the dynamics. The approach is applied to planar geometries with the use of an efficient multi-block, structured grid generation method to compute unsteady, two-dimensional and axisymmetric flow. The applications presented include the computation of the unsteady, inviscid flow about a hinged-flap with flap deflections and a high-speed inlet with centerbody motion as part of the unstart / restart operation

Non-Markovian Momentum Computing: Universal and Efficient

All computation is physically embedded. Reflecting this, a growing body of results embraces rate equations as the underlying mechanics of thermodynamic computation and biological information processing. Strictly applying the implied continuous-time Markov chains, however, excludes a universe of natural computing. We show that expanding the toolset to continuous-time hidden Markov chains substantially removes the constraints. The general point is made concrete by our analyzing two eminently-useful computations that are impossible to describe with a set of rate equations over the memory states. We design and analyze a thermodynamically-costless bit flip, providing a first counterexample to rate-equation modeling. We generalize this to a costless Fredkin gate---a key operation in reversible computing that is computation universal. Going beyond rate-equation dynamics is not only possible, but necessary if stochastic thermodynamics is to become part of the paradigm for physical information processing.Comment: 6 pages, 3 figures; Supplementary Material, 1 page; http://csc.ucdavis.edu/~cmg/compmech/pubs/cbdb.ht

Morphological Computation as Natural Ecosystem Service for Intelligent Technology

The basic idea of natural computing is learning from nature. The naturalist framework provides an info-computational architecture for cognizing agents, modeling living organisms as informational structures with computational dynamics. Intrinsic natural information processes can be used asnatural ecosystem services to perform resource-efficient computation, instead of explicitly controlling every step of the computational process. In robotics, morphological computing is using inherent material properties to produce behavior like passive walking or grasping. In general, morphology (structure, shape, form, material) is self-organizing into dynamic structures resulting in growth, development, and decision-making that represent processes of embodied cognition and constitute the naturalized basis of intelligent behavior

The natural, artificial, and social domains of intelligence: a triune approach

A “triune approach” to the three main domains of intelligence is advocated. It would be the most cogent way to understand the uses and impact of artificial intelligence in its intrinsic relation with human nature and social structures. The enormous technological success of artificial intelligence and the widespread social applications, impinging both in individual lives and in multiple economic and social structures, are making necessary a reflection on the wider dynamics of intelligence, interconnecting the artificial information pathways with the natural information flows and the social structural substrates. As a telling instance, the traditional poor understanding and management of “social emotions” is dangerously amplified in today’s social networks, contributing to unrest, polarization, and widespread desocialization processes. In contemporary societies, the essential link between intelligence and life has to be plainly revealed as a counterpoint to the link between artificial intelligence and computation