4,112 research outputs found
Pragmatic Holism
The reductionist/holist debate seems an impoverished one, with many participants appearing to adopt a position first and constructing rationalisations second. Here I propose an intermediate position of pragmatic holism, that irrespective of whether all natural systems are theoretically reducible, for many systems it is completely impractical to attempt such a reduction, also that regardless if whether irreducible `wholes' exist, it is vain to try and prove this in absolute terms. This position thus illuminates the debate along new pragmatic lines, and refocusses attention on the underlying heuristics of learning about the natural world
Verifying Recursive Active Documents with Positive Data Tree Rewriting
This paper proposes a data tree-rewriting framework for modeling evolving
documents. The framework is close to Guarded Active XML, a platform used for
handling XML repositories evolving through web services. We focus on automatic
verification of properties of evolving documents that can contain data from an
infinite domain. We establish the boundaries of decidability, and show that
verification of a {\em positive} fragment that can handle recursive service
calls is decidable. We also consider bounded model-checking in our data
tree-rewriting framework and show that it is \nexptime-complete
Computing with cells: membrane systems - some complexity issues.
Membrane computing is a branch of natural computing which abstracts computing models from the structure and the functioning of the living cell. The main ingredients of membrane systems, called P systems, are (i) the membrane structure, which consists of a hierarchical arrangements of membranes which delimit compartments where (ii) multisets of symbols, called objects, evolve according to (iii) sets of rules which are localised and associated with compartments. By using the rules in a nondeterministic/deterministic maximally parallel manner, transitions between the system configurations can be obtained. A sequence of transitions is a computation of how the system is evolving. Various ways of controlling the transfer of objects from one membrane to another and applying the rules, as well as possibilities to dissolve, divide or create membranes have been studied. Membrane systems have a great potential for implementing massively concurrent systems in an efficient way that would allow us to solve currently intractable problems once future biotechnology gives way to a practical bio-realization. In this paper we survey some interesting and fundamental complexity issues such as universality vs. nonuniversality, determinism vs. nondeterminism, membrane and alphabet size hierarchies, characterizations of context-sensitive languages and other language classes and various notions of parallelism
Visualizing Quantum Circuit Probability -- estimating computational action for quantum program synthesis
This research applies concepts from algorithmic probability to Boolean and
quantum combinatorial logic circuits. A tutorial-style introduction to states
and various notions of the complexity of states are presented. Thereafter, the
probability of states in the circuit model of computation is defined. Classical
and quantum gate sets are compared to select some characteristic sets. The
reachability and expressibility in a space-time-bounded setting for these gate
sets are enumerated and visualized. These results are studied in terms of
computational resources, universality and quantum behavior. The article
suggests how applications like geometric quantum machine learning, novel
quantum algorithm synthesis and quantum artificial general intelligence can
benefit by studying circuit probabilities.Comment: 17 page
Application of an evolutionary algorithm-based ensemble model to job-shop scheduling
In this paper, a novel evolutionary algorithm is applied to tackle job-shop scheduling tasks in manufacturing environments. Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-shop scheduling. The MmGA ensemble is able to approximate the optimal solution under the Pareto optimality principle. To evaluate the effectiveness of the MmGA ensemble, a case study based on real requirements is conducted. The results positively indicate the effectiveness of the MmGA ensemble in undertaking job-shop scheduling problems
Statistical Physics of Evolutionary Trajectories on Fitness Landscapes
Random walks on multidimensional nonlinear landscapes are of interest in many
areas of science and engineering. In particular, properties of adaptive
trajectories on fitness landscapes determine population fates and thus play a
central role in evolutionary theory. The topography of fitness landscapes and
its effect on evolutionary dynamics have been extensively studied in the
literature. We will survey the current research knowledge in this field,
focusing on a recently developed systematic approach to characterizing path
lengths, mean first-passage times, and other statistics of the path ensemble.
This approach, based on general techniques from statistical physics, is
applicable to landscapes of arbitrary complexity and structure. It is
especially well-suited to quantifying the diversity of stochastic trajectories
and repeatability of evolutionary events. We demonstrate this methodology using
a biophysical model of protein evolution that describes how proteins maintain
stability while evolving new functions
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