706 research outputs found
Can Machines Think in Radio Language?
People can think in auditory, visual and tactile forms of language, so can
machines principally. But is it possible for them to think in radio language?
According to a first principle presented for general intelligence, i.e. the
principle of language's relativity, the answer may give an exceptional solution
for robot astronauts to talk with each other in space exploration.Comment: 4 pages, 1 figur
Model of the Belousov-Zhabotinsky reaction
The article describes results of the modified model of the
Belousov-Zhabotinsky reaction, which resembles rather well the limit set
observed upon experimental performance of the reaction in the Petri dish. We
discuss the concept of the ignition of circular waves and show that only the
asymmetrical ignition leads to the formation of spiral structures. From the
qualitative assumptions on the behavior of dynamic systems, we conclude that
the Belousov-Zhabotinsky reaction likely forms a regular grid.Comment: 17 pages, 12 figure
Passing the Turing Test Does Not Mean the End of Humanity
In this paper we look at the phenomenon that is the Turing test. We consider how Turing originally introduced his imitation game and discuss what this means in a practical scenario. Due to its popular appeal we also look into different representations of the test as indicated by numerous reviewers. The main emphasis here, however, is to consider what it actually means for a machine to pass the Turing test and what importance this has, if any. In particular does it mean that, as Turing put it, a machine can âthinkâ. Specifically we consider claims that passing the Turing test means that machines will have achieved human-like intelligence and as a consequence the singularity will be upon us in the blink of an eye
Time-Efficient Read/Write Register in Crash-prone Asynchronous Message-Passing Systems
The atomic register is certainly the most basic object of computing science.
Its implementation on top of an n-process asynchronous message-passing system
has received a lot of attention. It has been shown that t \textless{} n/2
(where t is the maximal number of processes that may crash) is a necessary and
sufficient requirement to build an atomic register on top of a crash-prone
asynchronous message-passing system. Considering such a context, this paper
visits the notion of a fast implementation of an atomic register, and presents
a new time-efficient asynchronous algorithm. Its time-efficiency is measured
according to two different underlying synchrony assumptions. Whatever this
assumption, a write operation always costs a round-trip delay, while a read
operation costs always a round-trip delay in favorable circumstances
(intuitively, when it is not concurrent with a write). When designing this
algorithm, the design spirit was to be as close as possible to the one of the
famous ABD algorithm (proposed by Attiya, Bar-Noy, and Dolev)
Periodic pattern formation in reaction-diffusion systems -an introduction for numerical simulation
The aim of the present review is to provide a comprehensive explanation of Turing reactionâdiffusion systems in sufficient detail to allow readers to perform numerical calculations themselves. The reactionâdiffusion model is widely studied in the field of mathematical biology, serves as a powerful paradigm model for self-organization and is beginning to be applied to actual experimental systems in developmental biology. Despite the increase in current interest, the model is not well understood among experimental biologists, partly because appropriate introductory texts are lacking. In the present review, we provide a detailed description of the definition of the Turing reactionâdiffusion model that is comprehensible without a special mathematical background, then illustrate a method for reproducing numerical calculations with Microsoft Excel. We then show some examples of the patterns generated by the model. Finally, we discuss future prospects for the interdisciplinary field of research involving mathematical approaches in developmental biology
On the Executability of Interactive Computation
The model of interactive Turing machines (ITMs) has been proposed to
characterise which stream translations are interactively computable; the model
of reactive Turing machines (RTMs) has been proposed to characterise which
behaviours are reactively executable. In this article we provide a comparison
of the two models. We show, on the one hand, that the behaviour exhibited by
ITMs is reactively executable, and, on the other hand, that the stream
translations naturally associated with RTMs are interactively computable. We
conclude from these results that the theory of reactive executability subsumes
the theory of interactive computability. Inspired by the existing model of ITMs
with advice, which provides a model of evolving computation, we also consider
RTMs with advice and we establish that a facility of advice considerably
upgrades the behavioural expressiveness of RTMs: every countable transition
system can be simulated by some RTM with advice up to a fine notion of
behavioural equivalence.Comment: 15 pages, 0 figure
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How does predicate invention affect human comprehensibility?
During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses. Since predictive accuracy was readily measurable and comprehensibility not so, later definitions in the 1990s, such as that of Mitchell, tended to use a one-dimensional approach to Machine Learning based solely on predictive accuracy, ultimately favouring statistical over symbolic Machine Learning approaches. In this paper we provide a definition of comprehensibility of hypotheses which can be estimated using human participant trials. We present the results of experiments testing human comprehensibility of logic programs learned with and without predicate invention. Results indicate that comprehensibility is affected not only by the complexity of the presented program but also by the existence of anonymous predicate symbols
AI Researchers, Video Games Are Your Friends!
If you are an artificial intelligence researcher, you should look to video
games as ideal testbeds for the work you do. If you are a video game developer,
you should look to AI for the technology that makes completely new types of
games possible. This chapter lays out the case for both of these propositions.
It asks the question "what can video games do for AI", and discusses how in
particular general video game playing is the ideal testbed for artificial
general intelligence research. It then asks the question "what can AI do for
video games", and lays out a vision for what video games might look like if we
had significantly more advanced AI at our disposal. The chapter is based on my
keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad
audience.Comment: in Studies in Computational Intelligence Studies in Computational
Intelligence, Volume 669 2017. Springe
sCompile: Critical path identification and analysis for smart contracts
Ethereum smart contracts are an innovation built on top of the blockchain
technology, which provides a platform for automatically executing contracts in
an anonymous, distributed, and trusted way. The problem is magnified by the
fact that smart contracts, unlike ordinary programs, cannot be patched easily
once deployed. It is important for smart contracts to be checked against
potential vulnerabilities. In this work, we propose an alternative approach to
automatically identify critical program paths (with multiple function calls
including inter-contract function calls) in a smart contract, rank the paths
according to their criticalness, discard them if they are infeasible or
otherwise present them with user friendly warnings for user inspection. We
identify paths which involve monetary transaction as critical paths, and
prioritize those which potentially violate important properties. For
scalability, symbolic execution techniques are only applied to top ranked
critical paths. Our approach has been implemented in a tool called sCompile,
which has been applied to 36,099 smart contracts. The experiment results show
that sCompile is efficient, i.e., 5 seconds on average for one smart contract.
Furthermore, we show that many known vulnerabilities can be captured if user
inspects as few as 10 program paths generated by sCompile. Lastly, sCompile
discovered 224 unknown vulnerabilities with a false positive rate of 15.4%
before user inspection.Comment: Accepted by ICFEM 201
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Can Machine Intelligence be Measured in the Same Way as Human intelligence?
In recent years the number of research projects on computer programs solving human intelligence problems in artificial intelligence (AI), artificial general intelligence, as well as in Cognitive Modelling, has significantly grown. One reason could be the interest of such problems as benchmarks for AI algorithms. Another, more fundamental, motivation behind this area of research might be the (implicit) assumption that a computer program that successfully can solve human intelligence problems has human-level intelligence and vice versa. This paper analyses this assumption
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