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  • 1
    Electronic Resource
    Electronic Resource
    Backtracking with multi-level dynamic search rearrangement (1981)
    Springer
    Acta informatica 15 (1981), S. 99-113 
    Details
    ISSN: 1432-0525
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Summary The order in which the variables are tested in a backtrack program can have a major effect on its running time. The best search order usually varies among the branches of the backtrack tree, so the number of possible search orders can be astronomical. We present an algorithm that chooses a search order dynamically by investigating all possibilities for k levels below the current level, extending beyond k levels wherever possible by setting the variables that have unique forced values. The algorithm takes time O(n k+1) to process a node. For k=2 and binary variables the analysis for selecting the next variable to introduce into the backtrack tree makes complete use of the information contained in the two-level investigations. For larger k or variables of higher degree there is no polynomial-time algorithm that makes complete use of the k-level investigations to limit searching (unless P=NP). The search rearrangement algorithm is closely related to constraint propagation. Experimental studies on conjunctive normal form predicates confirm that 1-level search rearrangement saves a great deal of time compared to 0-level (ordinary backtracking), and show that 2-level saves time over 1-level on large problems. For such problems with 256 variables 2-level is better than 1-level by a factor of two.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00288958
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Parsing extended LR(k) grammars (1981)
    Springer
    Acta informatica 15 (1981), S. 115-127 
    Details
    ISSN: 1432-0525
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Summary An extended LR(k) (ELR(k)) grammar is a context free grammar in which the right sides of the productions are regular expressions and which can be parsed from left to right with k symbol look-ahead. We present a practical algorithm for producing small fast parsers directly from certain ELR(k) grammars, and an algorithm for converting the remaining ELR(k) grammars into a form that can be processed by the first algorithm. This method, when combined with previously developed methods for improving the efficiency of LR(k) parsers, usually produces parsers that are significantly smaller and faster than those produced by previous LR(k) and ELR(k) algorithms.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00288959
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  • 3
    Electronic Resource
    Electronic Resource
    Backtracking and random constraint satisfaction (1997)
    Springer
    Annals of mathematics and artificial intelligence 20 (1997), S. 393-410 
    Details
    ISSN: 1573-7470
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The average running time used by backtracking on random constraint satisfaction problems is studied. This time is polynomial when the ratio of constraints to variables is large, and it is exponential when the ratio is small. When the number of variables goes to infinity, whether the average time is exponential or polynomial depends on the number of variables per constraint, the number of values per variable, and the probability that a random setting of variables satisfies a constraint. A method for computing the curve that separates polynomial from exponential time and several methods for approximating the curve are given. The version of backtracking studied finds all solutions to a problem, so the running time is exponential when the number of solutions per problem is exponential. For small values of the probability, the curve that separates exponential and polynomial average running time coincides with the curve that separates an exponential average number of solutions from a polynomial number. For larger probabilities the two curves diverge. Random problems similar to those that arise in understanding line drawings with shadows require a time that is mildly exponential when they are solved by simple backtracking. Slightly more sophisticated algorithms (such as constraint propagation combined with backtracking) should be able to solve these rapidly.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1018944814355
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  • 4
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    Information, Vol. 7, Pages 41: Information and Meaning (2016)
    MDPI
    Details
    Publication Date: 2016-07-10
    Description: This paper considers the relationship between information and meaning through an analysis of a set of measures of information. Since meaning is expressed using information the analysis of the measures illuminates the relationship. The conventions that govern the production and exchange of information are the outcome of selection processes, so the quality of information (as expressed in the measures) is subject to limitations caused by selection. These limitations are analysed using a technique called viewpoint analysis that enables the measures and their relationship with meaning to be examined. Viewpoint analysis is applied to several logical paradoxes and resolves them in a manner consistent with common sense. Finally, the approach is used to address Floridi’s questions about the philosophy of information associated with meaning.
    Electronic ISSN: 2078-2489
    Topics: Computer Science
    Published by MDPI
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  • 5
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    Information, Vol. 9, Pages 332: Artificial Intelligence and the Limitations of Information (2018)
    MDPI
    Details
    Publication Date: 2018
    Description: Artificial intelligence (AI) and machine learning promise to make major changes to the relationship of people and organizations with technology and information. However, as with any form of information processing, they are subject to the limitations of information linked to the way in which information evolves in information ecosystems. These limitations are caused by the combinatorial challenges associated with information processing, and by the tradeoffs driven by selection pressures. Analysis of the limitations explains some current difficulties with AI and machine learning and identifies the principles required to resolve the limitations when implementing AI and machine learning in organizations. Applying the same type of analysis to artificial general intelligence (AGI) highlights some key theoretical difficulties and gives some indications about the challenges of resolving them.
    Electronic ISSN: 2078-2489
    Topics: Computer Science
    Published by MDPI
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  • 6
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    Information, Vol. 6, Pages 23-48: Measures of Information (2015)
    MDPI
    Details
    Publication Date: 2015-01-28
    Description: This paper builds an integrated framework of measures of information based on the Model for Information (MfI) developed by the author. Since truth is expressed using information, an analysis of truth depends on the nature of information and its limitations. These limitations include those implied by the geometry of information and those implied by the relativity of information. This paper proposes an approach to truth and truthlikeness that takes these limitations into account by incorporating measures of the quality of information. Another measure of information is the amount of information. This has played a role in two important theoretical difficulties—the Bar-Hillel Carnap paradox and the “scandal of deduction”. This paper further provides an analysis of the amount of information, based on MfI, and shows how the MfI approach can resolve these difficulties.
    Electronic ISSN: 2078-2489
    Topics: Computer Science
    Published by MDPI
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  • 7
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    Information, Vol. 5, Pages 479-507: A Model for Information (2014)
    MDPI
    Details
    Publication Date: 2014-09-19
    Description: This paper uses an approach drawn from the ideas of computer systems modelling to produce a model for information itself. The model integrates evolutionary, static and dynamic views of information and highlights the relationship between symbolic content and the physical world. The model includes what information technology practitioners call “non-functional” attributes, which, for information, include information quality and information friction. The concepts developed in the model enable a richer understanding of Floridi’s questions “what is information?” and “the informational circle: how can information be assessed?” (which he numbers P1 and P12).
    Electronic ISSN: 2078-2489
    Topics: Computer Science
    Published by MDPI
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  • 8
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    Information, Vol. 6, Pages 733-749: Digital Information and Value (2015)
    MDPI
    Details
    Publication Date: 2015-11-11
    Description: Digital information changes the ways in which people and organisations interact. This paper examines the nature of this change in the context of the author’s Model for Information (MfI). It investigates the relationship between outcomes and value, selection processes and some attributes of information and explores how this relationship changes in the move from analogue to digital information. Selection processes shape the evolution of information ecosystems in which conventions are established for the ways in which information is used. The conventions determine norms for information friction and information quality as well as the sources of information and channels used. Digital information reduces information friction, often dramatically, and changes information quality. The increasing use of analytics in business increasingly delivers predictive or prescriptive digital information. These changes are happening faster than information ecosystem conventions can change. The relationships established in the paper enable an analysis of, and guide changes to, these conventions enabling a more effective use of digital information.
    Electronic ISSN: 2078-2489
    Topics: Computer Science
    Published by MDPI
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  • 9
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    Information, Vol. 10, Pages 393: Information Evolution and Organisations (2019)
    MDPI
    Details
    Publication Date: 2019
    Description: In a changing digital world, organisations need to be effective information processing entities, in which people, processes, and technology together gather, process, and deliver the information that the organisation needs. However, like other information processing entities, organisations are subject to the limitations of information evolution. These limitations are caused by the combinatorial challenges associated with information processing, and by the trade-offs and shortcuts driven by selection pressures. This paper applies the principles of information evolution to organisations and uses them to derive principles about organisation design and organisation change. This analysis shows that information evolution can illuminate some of the seemingly intractable difficulties of organisations, including the effects of organisational silos and the difficulty of organisational change. The derived principles align with and connect different strands of current organisational thinking. In addition, they provide a framework for creating analytical tools to create more detailed organisational insights.
    Electronic ISSN: 2078-2489
    Topics: Computer Science
    Published by MDPI
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  • 10
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    Information, Vol. 8, Pages 61: Information and Inference (2017)
    MDPI
    Details
    Publication Date: 2017-05-28
    Description: Inference is expressed using information and is therefore subject to the limitations of information. The conventions that determine the reliability of inference have developed in information ecosystems under the influence of a range of selection pressures. These conventions embed limitations in information measures like quality, pace and friction caused by selection trade-offs. Some selection pressures improve the reliability of inference; others diminish it by reinforcing the limitations of the conventions. This paper shows how to apply these ideas to inference in order to analyse the limitations; the analysis is applied to various theories of inference including examples from the philosophies of science and mathematics as well as machine learning. The analysis highlights the limitations of these theories and how different, seemingly competing, ideas about inference can relate to each other.
    Electronic ISSN: 2078-2489
    Topics: Computer Science
    Published by MDPI
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