Quantifying Resource Use in Computations

It is currently not possible to quantify the resources needed to perform a computation. As a consequence, it is not possible to reliably evaluate the hardware resources needed for the application of algorithms or the running of programs. This is apparent in both computer science, for instance, in cryptanalysis, and in neuroscience, for instance, comparative neuro-anatomy. A System versus Environment game formalism is proposed based on Computability Logic that allows to define a computational work function that describes the theoretical and physical resources needed to perform any purely algorithmic computation. Within this formalism, the cost of a computation is defined as the sum of information storage over the steps of the computation. The size of the computational device, eg, the action table of a Universal Turing Machine, the number of transistors in silicon, or the number and complexity of synapses in a neural net, is explicitly included in the computational cost. The proposed cost function leads in a natural way to known computational trade-offs and can be used to estimate the computational capacity of real silicon hardware and neural nets. The theory is applied to a historical case of 56 bit DES key recovery, as an example of application to cryptanalysis. Furthermore, the relative computational capacities of human brain neurons and the C. elegans nervous system are estimated as an example of application to neural nets.Comment: 26 pages, no figure

Current Density Imaging through Acoustically Encoded Magnetometry: A Theoretical Exploration

The problem of determining a current density confined to a volume from measurements of the magnetic field it produces exterior to that volume is known to have non-unique solutions. To uniquely determine the current density, or the non-silent components of it, additional spatial encoding of the electric current is needed. In biological systems such as the brain and heart, which generate electric current associated with normal function, a reliable means of generating such additional encoding, on a spatial and temporal scale meaningful to the study of such systems, would be a boon for research. This paper explores a speculative method by which the required additional encoding might be accomplished, on the time scale associated with the propagation of sound across the volume of interest, by means of the application of a radially encoding pulsed acoustic spherical wave

Asimov's Coming Back

Ever since the word ‘ROBOT’ first appeared in a science\ud fiction in 1921, scientists and engineers have been trying\ud different ways to create it. Present technologies in\ud mechanical and electrical engineering makes it possible\ud to have robots in such places as industrial manufacturing\ud and assembling lines. Although they are\ud essentially robotic arms or similarly driven by electrical\ud power and signal control, they could be treated the\ud primitive pioneers in application. Researches in the\ud laboratories go much further. Interdisciplines are\ud directing the evolution of more advanced robots. Among these are artificial\ud intelligence, computational neuroscience, mathematics and robotics. These disciplines\ud come closer as more complex problems emerge.\ud From a robot’s point of view, three basic abilities are needed. They are thinking\ud and memory, sensory perceptions, control and behaving. These are capabilities we\ud human beings have to adapt ourselves to the environment. Although\ud researches on robots, especially on intelligent thinking, progress slowly, a revolution\ud for biological inspired robotics is spreading out in the laboratories all over the world