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Emmanuelle-anna Dietz - One of the best experts on this subject based on the ideXlab platform.
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a Computational Logic approach to the belief bias in human syllogistic reasoning
Contexts, 2017Co-Authors: Emmanuelle-anna DietzAbstract:PsychoLogical experiments on syllogistic reasoning have shown that participants did not always deduce the classical Logically valid conclusions. In particular, the results show that they had difficulties to reason with syllogistic statements that contradicted their own beliefs. We consider a syllogistic reasoning task carried out by Evans, Barston and Pollard, who investigated the belief-bias effect with respect to syllogisms. We propose a formalization of the belief-bias effect for human syllogistic reasoning under the Weak Completion Semantics, a Logic programming approach that aims at adequately modeling human reasoning.
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a new Computational Logic approach to reason with conditionals
International Conference on Logic Programming, 2015Co-Authors: Emmanuelle-anna Dietz, Steffen HölldoblerAbstract:We present a new approach to evaluate conditionals in human reasoning. This approach is based on the weak completion semantics which has been successfully applied to adequately model various other human reasoning tasks in the past. The main idea is to explicitly consider the case, where the condition of a conditional is unknown with respect to some background knowledge, and to evaluate it with minimal revision followed by abduction. We formally compare our approach to a recent approach by Schulz and demonstrate that our proposal is superior in that it can handle more human reasoning tasks.
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A Computational Logic Approach to Human Spatial Reasoning
2015 IEEE Symposium Series on Computational Intelligence, 2015Co-Authors: Emmanuelle-anna Dietz, Steffen Hölldobler, Raphael HöpsAbstract:We present a new approach with respect to spatial reasoning problems by using Logic programs. Because the weak completion of a Logic program admits a least model under the three-valued Lukasiewicz semantics and this semantics has been successfully applied to other human reasoning tasks, conditionals are evaluated under these least L-models. We show that the weak completion semantics can also handle spatial relations in a way humans do. In particular, we develop a Computational Logic approach to spatial reasoning and show that the weak completion semantics computes preferred mental models.
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a Computational Logic approach to the suppression task
Cognitive Science, 2012Co-Authors: Emmanuelle-anna Dietz, Steffen Hölldobler, Marco RagniAbstract:A Computational Logic Approach to the Suppression Task Emmanuelle-Anna Dietz and Steffen H¨olldobler ({dietz,sh}@iccl.tu-dresden.de) International Center for Computation Logic, TU Dresden D-01062 Dresden, Germany Marco Ragni (ragni@cognition.uni-freiburg.de) Center for Cognitive Science, Friedrichstrase 50 D-79098 Freiburg, Germany Table 1: The suppression task (Byrne, 1989) and used abbre- viations. Subjects received conditionals A, B or C and facts E, E,L or L and had to draw inferences. Abstract A novel approach to human conditional reasoning based on the three-valued Łukasiewicz Logic is presented. We will demon- strate that the Łukasiewicz Logic overcomes problems the so- far proposed Fitting Logic has in reasoning with the suppres- sion task. While adequately solving the suppression task, the approach gives rise to a number of open questions concerning the use of Łukasiewicz Logic, unique fixed points, completion versus weak completion, explanations, negation, and sceptical versus credulous approaches in human reasoning. A B C E E L L Keywords: Łukasiewicz Logic; Computational Logic; suppres- sion task; human reasoning. Introduction An interesting study is the suppression task, in which Byrne (1989) has shown that graduate students with no previous ex- posure to formal Logic did suppress previously drawn conclu- sions when additional information became available. Inter- estingly, in some instances the previously drawn conclusions were valid whereas in other instances the conclusions were invalid with respect to classical two-valued Logic. Consider the following example: If she has an essay to finish then she will study late in the library and She has an essay to finish. Then most subjects (96%) conclude: She will study late in the library. If subjects, however, receive an additional condi- tional: If the library stays open she will study late in the li- brary then only 38% of the subjects conclude: She will study late in the library. This shows, that, although the conclusion is still correct, the conclusion is suppressed by an additional conditional. This is an excellent example for human capabil- ity to draw non-monotonic inferences. Table 1 shows the abbreviations that will be used through- out the paper, whereas Table 2 gives an account of the find- ings of Byrne (1989). As we are using a formal language, propositions like “She will go to the library” (abbreviated L) will be represented by propositional variables like l, with the intended interpretation that if l is true (>), then “She will go to the library”. Taking a naive propositional approach, we can represent A by the implication e ← l, where the propositional variables e and l represent the facts E and L, respectively, and so on. It is straightforward to see that classical two-valued Logic cannot model the suppression task adequately: Applying the classical Logical consequence operator to some instances of the suppression task (like A, C, E) yields qualitatively wrong answers, due to the monotonic nature of the classical Logic. If she has an essay to finish then she will study late in the library. If she has a textbook to read then she will study late in the library. If the library stays open she will study late in the library. She has an essay to finish. She does not have an essay to finish. She will study late in the library. She will not study late in the library. Table 2: The drawn conclusions in the experiment of Byrne. Conditional(s) Fact Experimental Findings A A, B A, C E E E 96% of subjects conclude L. 96% of subjects conclude L. 38% of subjects conclude L. A A, B A, C E E E 46% of subjects conclude L. 4% of subjects conclude L. 63% of subjects conclude L. A A, B A, C L L L 53% of subjects conclude E. 16% of subjects conclude E. 55% of subjects conclude E. A A, B A, C L L L 69% of subjects conclude E. 69% of subjects conclude E. 44% of subjects conclude E. Consequently, at least a non-monotonic operator is needed. As argued by Stenning and van Lambalgen (2008) 1 human reasoning should be modeled by, first, reasoning towards an appropriate representation and, second, by reasoning with re- spect to this representation. As appropriate representation Stenning and van Lambalgen propose Logic programs under completion semantics based on the three-valued Logic used by Fitting (1985), which itself is based on the three-valued Kleene (1952) Logic. Unfortunately, some technical claims made by Stenning and van Lambalgen (2008) are wrong concerning their sec- ond step. H¨olldobler and Kencana Ramli (2009b) have shown that the three-valued Logic proposed by Fitting is inadequate for the suppression task. Somewhat surprisingly, the sup- pression task can be adequately modeled if the three-valued 1 There is an earlier publication (Stenning & van Lambalgen, 2005), but Michiel van Lambalgen advised us to refer to their text- book.
Steffen Hölldobler - One of the best experts on this subject based on the ideXlab platform.
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the syllogistic reasoning task reasoning principles and heuristic strategies in modeling human clusters
DECLARE, 2017Co-Authors: Emmanuelleanna Dietz Saldanha, Steffen Hölldobler, Richard MorbitzAbstract:It seems widely accepted that human reasoning cannot be modeled by means of classical Logic. PsychoLogical experiments have repeatedly shown that participants’ answers systematically deviate from the classical Logically correct answers. Recently, a new Computational Logic approach to modeling human syllogistic reasoning has been developed which seems to perform better than other state-of-the-art cognitive theories. We take this approach as starting point, yet instead of trying to model the human reasoner, we aim at identifying clusters of reasoners, which can be characterized by reasoning principles or by heuristic strategies.
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a new Computational Logic approach to reason with conditionals
International Conference on Logic Programming, 2015Co-Authors: Emmanuelle-anna Dietz, Steffen HölldoblerAbstract:We present a new approach to evaluate conditionals in human reasoning. This approach is based on the weak completion semantics which has been successfully applied to adequately model various other human reasoning tasks in the past. The main idea is to explicitly consider the case, where the condition of a conditional is unknown with respect to some background knowledge, and to evaluate it with minimal revision followed by abduction. We formally compare our approach to a recent approach by Schulz and demonstrate that our proposal is superior in that it can handle more human reasoning tasks.
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A Computational Logic Approach to Human Spatial Reasoning
2015 IEEE Symposium Series on Computational Intelligence, 2015Co-Authors: Emmanuelle-anna Dietz, Steffen Hölldobler, Raphael HöpsAbstract:We present a new approach with respect to spatial reasoning problems by using Logic programs. Because the weak completion of a Logic program admits a least model under the three-valued Lukasiewicz semantics and this semantics has been successfully applied to other human reasoning tasks, conditionals are evaluated under these least L-models. We show that the weak completion semantics can also handle spatial relations in a way humans do. In particular, we develop a Computational Logic approach to spatial reasoning and show that the weak completion semantics computes preferred mental models.
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a Computational Logic approach to the suppression task
Cognitive Science, 2012Co-Authors: Emmanuelle-anna Dietz, Steffen Hölldobler, Marco RagniAbstract:A Computational Logic Approach to the Suppression Task Emmanuelle-Anna Dietz and Steffen H¨olldobler ({dietz,sh}@iccl.tu-dresden.de) International Center for Computation Logic, TU Dresden D-01062 Dresden, Germany Marco Ragni (ragni@cognition.uni-freiburg.de) Center for Cognitive Science, Friedrichstrase 50 D-79098 Freiburg, Germany Table 1: The suppression task (Byrne, 1989) and used abbre- viations. Subjects received conditionals A, B or C and facts E, E,L or L and had to draw inferences. Abstract A novel approach to human conditional reasoning based on the three-valued Łukasiewicz Logic is presented. We will demon- strate that the Łukasiewicz Logic overcomes problems the so- far proposed Fitting Logic has in reasoning with the suppres- sion task. While adequately solving the suppression task, the approach gives rise to a number of open questions concerning the use of Łukasiewicz Logic, unique fixed points, completion versus weak completion, explanations, negation, and sceptical versus credulous approaches in human reasoning. A B C E E L L Keywords: Łukasiewicz Logic; Computational Logic; suppres- sion task; human reasoning. Introduction An interesting study is the suppression task, in which Byrne (1989) has shown that graduate students with no previous ex- posure to formal Logic did suppress previously drawn conclu- sions when additional information became available. Inter- estingly, in some instances the previously drawn conclusions were valid whereas in other instances the conclusions were invalid with respect to classical two-valued Logic. Consider the following example: If she has an essay to finish then she will study late in the library and She has an essay to finish. Then most subjects (96%) conclude: She will study late in the library. If subjects, however, receive an additional condi- tional: If the library stays open she will study late in the li- brary then only 38% of the subjects conclude: She will study late in the library. This shows, that, although the conclusion is still correct, the conclusion is suppressed by an additional conditional. This is an excellent example for human capabil- ity to draw non-monotonic inferences. Table 1 shows the abbreviations that will be used through- out the paper, whereas Table 2 gives an account of the find- ings of Byrne (1989). As we are using a formal language, propositions like “She will go to the library” (abbreviated L) will be represented by propositional variables like l, with the intended interpretation that if l is true (>), then “She will go to the library”. Taking a naive propositional approach, we can represent A by the implication e ← l, where the propositional variables e and l represent the facts E and L, respectively, and so on. It is straightforward to see that classical two-valued Logic cannot model the suppression task adequately: Applying the classical Logical consequence operator to some instances of the suppression task (like A, C, E) yields qualitatively wrong answers, due to the monotonic nature of the classical Logic. If she has an essay to finish then she will study late in the library. If she has a textbook to read then she will study late in the library. If the library stays open she will study late in the library. She has an essay to finish. She does not have an essay to finish. She will study late in the library. She will not study late in the library. Table 2: The drawn conclusions in the experiment of Byrne. Conditional(s) Fact Experimental Findings A A, B A, C E E E 96% of subjects conclude L. 96% of subjects conclude L. 38% of subjects conclude L. A A, B A, C E E E 46% of subjects conclude L. 4% of subjects conclude L. 63% of subjects conclude L. A A, B A, C L L L 53% of subjects conclude E. 16% of subjects conclude E. 55% of subjects conclude E. A A, B A, C L L L 69% of subjects conclude E. 69% of subjects conclude E. 44% of subjects conclude E. Consequently, at least a non-monotonic operator is needed. As argued by Stenning and van Lambalgen (2008) 1 human reasoning should be modeled by, first, reasoning towards an appropriate representation and, second, by reasoning with re- spect to this representation. As appropriate representation Stenning and van Lambalgen propose Logic programs under completion semantics based on the three-valued Logic used by Fitting (1985), which itself is based on the three-valued Kleene (1952) Logic. Unfortunately, some technical claims made by Stenning and van Lambalgen (2008) are wrong concerning their sec- ond step. H¨olldobler and Kencana Ramli (2009b) have shown that the three-valued Logic proposed by Fitting is inadequate for the suppression task. Somewhat surprisingly, the sup- pression task can be adequately modeled if the three-valued 1 There is an earlier publication (Stenning & van Lambalgen, 2005), but Michiel van Lambalgen advised us to refer to their text- book.
David Dornfeld - One of the best experts on this subject based on the ideXlab platform.
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life cycle assessment of Computational Logic produced from 1995 through 2010
Environmental Research Letters, 2010Co-Authors: Sarah Boyd, Arpad Horvath, David DornfeldAbstract:Determination of the life-cycle environmental and human health impacts of semiconductor Logic is essential to a better understanding of the role information technology can play in achieving energy efficiency or global warming potential reduction goals. This study provides a life-cycle assessment for digital Logic chips over seven technology generations, spanning from 1995 through 2010. Environmental indicators include global warming potential, acidification, eutrophication, ground-level ozone (smog) formation, potential human cancer and non-cancer health effects, ecotoxicity and water use. While impacts per device area related to fabrication infrastructure and use-phase electricity have increased steadily, those due to transportation and fabrication direct emissions have fallen as a result of changes in process technology, device and wafer sizes and yields over the generations. Electricity, particularly in the use phase, and direct emissions from fabrication are the most important contributors to life-cycle impacts. Despite the large quantities of water used in fabrication, across the life cycle, the largest fraction of water is consumed in generation of electricity for use-phase power. Reducing power consumption in the use phase is the most effective way to limit impacts, particularly for the more recent generations of Logic.
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Life-cycle energy demand and global warming potential of Computational Logic
Environmental Science and Technology, 2009Co-Authors: Sarah B. Boyd, Arpad Horvath, David DornfeldAbstract:Computational Logic, in the form of semiconductor chips of the complementary metal oxide semiconductor (CMOS) transistor structure, is used in personal computers, wireless devices, IT network infrastructure, and nearly all modem electronics. This study provides a life-cycle energy analysis for CMOS chips over 7 technology generations with the purpose of comparing energy demand and global warming potential (GWP) impacts of the life-cycle stages, examining trends in these impacts over time and evaluating their sensitivity to data uncertainty and changes in production metrics such as yield. A hybrid life-cycle assessment (LCA) model is used. While life-cycle energy and GWP of emissions have increased on the basis of a wafer or die, these impacts have been reducing per unit of Computational power. Sensitivity analysis of the model shows that impacts have the highest relative sensitivity to wafer yield, line yield, and die size and largest absolute sensitivity to the use-phase power demand of the chip.
Jose Meseguer - One of the best experts on this subject based on the ideXlab platform.
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dependency pairs for proving termination properties of conditional term rewriting systems
The Journal of Logic and Algebraic Programming, 2017Co-Authors: Salvador Lucas, Jose MeseguerAbstract:Abstract The notion of operational termination provides a Logic-based definition of termination of Computational systems as the absence of infinite inferences in the Computational Logic describing the operational semantics of the system. For Conditional Term Rewriting Systems we show that operational termination is characterized as the conjunction of two termination properties. One of them is traditionally called termination and corresponds to the absence of infinite sequences of rewriting steps (a horizontal dimension). The other property, that we call V-termination, concerns the absence of infinitely many attempts to launch the subsidiary processes that are required to perform a single rewriting step (a vertical dimension). We introduce appropriate notions of dependency pairs to characterize termination, V-termination, and operational termination of Conditional Term Rewriting Systems. This can be used to obtain a powerful and more expressive framework for proving termination properties of Conditional Term Rewriting Systems.
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a rewriting Logic approach to operational semantics
Information & Computation, 2009Co-Authors: Traian Florin şerbănuţă, Grigore Rosu, Jose MeseguerAbstract:This paper shows how rewriting Logic semantics (RLS) can be used as a Computational Logic framework for operational semantic definitions of programming languages. Several operational semantics styles are addressed: big-step and small-step structural operational semantics (SOS), modular SOS, reduction semantics with evaluation contexts, continuation-based semantics, and the chemical abstract machine. Each of these language definitional styles can be faithfully captured as an RLS theory, in the sense that there is a one-to-one correspondence between Computational steps in the original language definition and Computational steps in the corresponding RLS theory. A major goal of this paper is to show that RLS does not force or pre-impose any given language definitional style, and that its flexibility and ease of use makes RLS an appealing framework for exploring new definitional styles.
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a rewriting Logic approach to operational semantics extended abstract
Electronic Notes in Theoretical Computer Science, 2007Co-Authors: Traian Florin şerbănuţă, Grigore Rosu, Jose MeseguerAbstract:This paper shows how rewriting Logic semantics (RLS) can be used as a Computational Logic framework for operational semantic definitions of programming languages. Several operational semantics styles are addressed: big-step and small-step structural operational semantics (SOS), modular SOS, reduction semantics with evaluation contexts, and continuation-based semantics. Each of these language definitional styles can be faithfully captured as an RLS theory, in the sense that there is a one-to-one correspondence between Computational steps in the original language definition and Computational steps in the corresponding RLS theory. A major goal of this paper is to show that RLS does not force or pre-impose any given language definitional style, and that its flexibility and ease of use makes RLS an appealing framework for exploring new definitional styles.
David Robertson - One of the best experts on this subject based on the ideXlab platform.
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multi agent coordination as distributed Logic programming
International Conference on Logic Programming, 2004Co-Authors: David RobertsonAbstract:A novel style of multi-agent system specification and deployment is described, in which familiar methods from Computational Logic are re-interpreted to a new context. One view of multi-agent system design is that coordination is achieved via an interaction model in which participating agents assume roles constrained by the social norms of their shared task; the state of the interaction reflecting the ways these constraints are mutually satisfied within some system for synchronisation that is open and distributed. We show how to harness a process calculus; constraint solving; unfolding and meta-variables for this purpose and discuss the advantages of these methods over traditional approaches.