Results 11  20
of
1,361
A DNA and restriction enzyme implementation of Turing Machines.
 DIMACS SERIES IN DISCRETE MATHEMATICS AND THEORETICAL COMPUTER SCIENCE
"... Bacteria employ restriction enzymes to cut or restrict DNA at or near specific words in a unique way. Many restriction enzymes cut the two strands of doublestranded DNA at different positions leaving overhangs of singlestranded DNA. Two pieces of DNA may be rejoined or ligated if their terminal ov ..."
Abstract

Cited by 80 (1 self)
 Add to MetaCart
Bacteria employ restriction enzymes to cut or restrict DNA at or near specific words in a unique way. Many restriction enzymes cut the two strands of doublestranded DNA at different positions leaving overhangs of singlestranded DNA. Two pieces of DNA may be rejoined or ligated if their terminal overhangs are complementary. Using these operations fragments of DNA, or oligonucleotides, may be inserted and deleted from a circular piece of plasmid DNA. We propose an encoding for the transition table of a Turing machine in DNA oligonucleotides and a corresponding series of restrictions and ligations of those oligonucleotides that, when performed on circular DNA encoding an instantaneous description of a Turing machine, simulate the operation of the Turing machine encoded in those oligonucleotides. DNA based Turing machines have been proposed by Charles Bennett but they invoke imaginary enzymes to perform the statesymbol transitions. Our approach differs in that every operation can be pe...
Special Purpose Parallel Computing
 Lectures on Parallel Computation
, 1993
"... A vast amount of work has been done in recent years on the design, analysis, implementation and verification of special purpose parallel computing systems. This paper presents a survey of various aspects of this work. A long, but by no means complete, bibliography is given. 1. Introduction Turing ..."
Abstract

Cited by 77 (5 self)
 Add to MetaCart
A vast amount of work has been done in recent years on the design, analysis, implementation and verification of special purpose parallel computing systems. This paper presents a survey of various aspects of this work. A long, but by no means complete, bibliography is given. 1. Introduction Turing [365] demonstrated that, in principle, a single general purpose sequential machine could be designed which would be capable of efficiently performing any computation which could be performed by a special purpose sequential machine. The importance of this universality result for subsequent practical developments in computing cannot be overstated. It showed that, for a given computational problem, the additional efficiency advantages which could be gained by designing a special purpose sequential machine for that problem would not be great. Around 1944, von Neumann produced a proposal [66, 389] for a general purpose storedprogram sequential computer which captured the fundamental principles of...
Evolving Algebras: An Attempt To Discover Semantics
, 1993
"... Machine (a virtual machine model which underlies most of the current Prolog implementations and incorporates crucial optimization techniques) starting from a more abstract EA for Prolog developed by Borger in [Bo1Bo3]. Q: How do you tailor an EA machine to the abstraction level of an algorithm wh ..."
Abstract

Cited by 74 (11 self)
 Add to MetaCart
Machine (a virtual machine model which underlies most of the current Prolog implementations and incorporates crucial optimization techniques) starting from a more abstract EA for Prolog developed by Borger in [Bo1Bo3]. Q: How do you tailor an EA machine to the abstraction level of an algorithm whose individual steps are complicated algorithms all by themselves? For example, the algorithm may be written in a high level language that allows, say, multiplying integer matrices in one step. A: You model the given algorithm modulo those algorithms needed to perform single steps. In your case, matrix multiplication will be built in as an operation. Q: Coming back to Turing, there could be a good reason for him to speak about computable functions rather than algorithms. We don't really know what algorithms are. A: I agree. Notice, however, that there are different notions of algorithm. On the one hand, an algorithm is an intuitive idea which you have in your head before writing code. Th...
The fully informed particle swarm: Simpler, maybe better
 IEEE Transactions on Evolutionary Computation
, 2004
"... The canonical particle swarm algorithm is a new approach to optimization, drawing inspiration from group behavior and the establishment of social norms. It is gaining popularity, especially because of the speed of convergence and the fact it is easy to use. However, we feel that each individual is n ..."
Abstract

Cited by 73 (3 self)
 Add to MetaCart
(Show Context)
The canonical particle swarm algorithm is a new approach to optimization, drawing inspiration from group behavior and the establishment of social norms. It is gaining popularity, especially because of the speed of convergence and the fact it is easy to use. However, we feel that each individual is not simply influenced by the best performer among his neighbors. We thus decided to make the individuals “fully informed. ” The results are very promising, as informed individuals seem to find better solutions in all the benchmark functions.
Minimum Description Length Induction, Bayesianism, and Kolmogorov Complexity
 IEEE Transactions on Information Theory
, 1998
"... The relationship between the Bayesian approach and the minimum description length approach is established. We sharpen and clarify the general modeling principles MDL and MML, abstracted as the ideal MDL principle and defined from Bayes's rule by means of Kolmogorov complexity. The basic conditi ..."
Abstract

Cited by 70 (7 self)
 Add to MetaCart
The relationship between the Bayesian approach and the minimum description length approach is established. We sharpen and clarify the general modeling principles MDL and MML, abstracted as the ideal MDL principle and defined from Bayes's rule by means of Kolmogorov complexity. The basic condition under which the ideal principle should be applied is encapsulated as the Fundamental Inequality, which in broad terms states that the principle is valid when the data are random, relative to every contemplated hypothesis and also these hypotheses are random relative to the (universal) prior. Basically, the ideal principle states that the prior probability associated with the hypothesis should be given by the algorithmic universal probability, and the sum of the log universal probability of the model plus the log of the probability of the data given the model should be minimized. If we restrict the model class to the finite sets then application of the ideal principle turns into Kolmogorov's mi...
Routines and other recurring action patterns of organizations: Contemporary research issues
 Industrial and Corporate Change
, 1996
"... This paper reports and extends discussions carried out during a workshop held at the Santa Fe Institute in August 1995 by the authors. It treats eight major topics: (i) the importance of carefully examining research on routine, (it) the concept of 'action patterns ' in general and in terms ..."
Abstract

Cited by 64 (10 self)
 Add to MetaCart
This paper reports and extends discussions carried out during a workshop held at the Santa Fe Institute in August 1995 by the authors. It treats eight major topics: (i) the importance of carefully examining research on routine, (it) the concept of 'action patterns ' in general and in terms of routine, (Hi) the useful categorization of routines and other recurring patterns, (iv) the research implications of recent cognitive results, (v) the relation of evolution to action patterns, (vi) the contributions of simulation modeling for theory in this area, (vii) examples of various approaches to empirical jj; research that reveal key problems, and (viii) a possible definition of 'routine'. An m extended appendix by Massimo Egidi provides a lexicon of synonyms and opposites ji covering use of the word 'routine ' in such areas as economics, organization theory and z artificial intelligence. 6
Optimal Ordered Problem Solver
, 2002
"... We present a novel, general, optimally fast, incremental way of searching for a universal algorithm that solves each task in a sequence of tasks. The Optimal Ordered Problem Solver (OOPS) continually organizes and exploits previously found solutions to earlier tasks, eciently searching not only the ..."
Abstract

Cited by 61 (20 self)
 Add to MetaCart
(Show Context)
We present a novel, general, optimally fast, incremental way of searching for a universal algorithm that solves each task in a sequence of tasks. The Optimal Ordered Problem Solver (OOPS) continually organizes and exploits previously found solutions to earlier tasks, eciently searching not only the space of domainspecific algorithms, but also the space of search algorithms. Essentially we extend the principles of optimal nonincremental universal search to build an incremental universal learner that is able to improve itself through experience.
Automating Software Feature Verification
 BELL LABS TECHNICAL JOURNAL
, 2000
"... A significant part of the call processing software for Lucent's new PathStar access server [FSW98] was checked with automated formal verification techniques. The verification system we built for this purpose, named FeaVer, maintains a database of feature requirements which is accessible via ..."
Abstract

Cited by 60 (15 self)
 Add to MetaCart
A significant part of the call processing software for Lucent's new PathStar access server [FSW98] was checked with automated formal verification techniques. The verification system we built for this purpose, named FeaVer, maintains a database of feature requirements which is accessible via a web browser. Via the browser the user can invoke verification runs. The verifications are performed by the system with the help of a standard logic model checker that runs in the background, invisibly to the user. Requirement violations are reported as C execution traces and stored in the database for user perusal and correction. The main strength of the system is in the detection of undesired feature interactions at an early stage of systems design, the type of problem that is notoriously difficult to detect with traditional testing techniques. Error reports
The Computational Power and Complexity of Constraint Handling Rules
 In Second Workshop on Constraint Handling Rules, at ICLP05
, 2005
"... Constraint Handling Rules (CHR) is a highlevel rulebased programming language which is increasingly used for general purposes. We introduce the CHR machine, a model of computation based on the operational semantics of CHR. Its computational power and time complexity properties are compared to thos ..."
Abstract

Cited by 54 (23 self)
 Add to MetaCart
Constraint Handling Rules (CHR) is a highlevel rulebased programming language which is increasingly used for general purposes. We introduce the CHR machine, a model of computation based on the operational semantics of CHR. Its computational power and time complexity properties are compared to those of the wellunderstood Turing machine and Random Access Memory machine. This allows us to prove the interesting result that every algorithm can be implemented in CHR with the best known time and space complexity. We also investigate the practical relevance of this result and the constant factors involved. Finally we expand the scope of the discussion to other (declarative) programming languages.
Logical Depth and Physical Complexity
 THE UNIVERSAL TURING MACHINE: A HALFCENTURY SURVEY
, 1988
"... Some mathematical and natural objects (a random sequence, a sequence of zeros, a perfect crystal, a gas) are intuitively trivial, while others (e.g. the human body, the digits of #) contain internal evidence of a nontrivial causal history. We formalize this ..."
Abstract

Cited by 54 (0 self)
 Add to MetaCart
Some mathematical and natural objects (a random sequence, a sequence of zeros, a perfect crystal, a gas) are intuitively trivial, while others (e.g. the human body, the digits of #) contain internal evidence of a nontrivial causal history. We formalize this