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Joshua Mugg - One of the best experts on this subject based on the ideXlab platform.

  • CogSci - Simultaneous Contradictory Belief and the Two-Systems Hypothesis
    Cognitive Science, 2020
    Co-Authors: Joshua Mugg
    Abstract:

    Simultaneous Contradictory Belief and the Two-System Hypothesis Joshua Mugg (joshuamugg@gmail.com) Department of Philosophy, 4700 Keele St. Toronto, ON M3J 1P3 Canada criticism of the two-system hypothesis has focused on the kind claim (Samuels 2009; Evans 2011), I argue that Sloman has not provided us with cases of SCB. I then offer an experimental setup that would strongly support the existence of SBC. Abstract The two-system hypothesis states that there are two kinds of reasoning systems, the first of which is evolutionarily old, heuristically (or associatively) based, automatic, fast, and is a collection of independent systems. The second is evolutionarily new, perhaps peculiar to humans, is rule-based, controlled, slow, and is a single token system. Advocates of the two-system hypothesis generally support their claim by an inference to the best explanation: two systems are needed to explain experimental data from the reasoning, heuristics, and biases literature. The best evidence for this claim comes from simultaneous Contradictory Belief (henceforth SCB) (Sloman 1996, 2002). I argue that Sloman has not provided us with cases of SCB. In each of his examples there is no evidence that the Beliefs are held simultaneously. I then offer the outline for an experimental setup that would offer compelling evidence for the existence of SCB and thereby support the two-system hypothesis. Keywords: Dual-process; two-system simultaneous Contradictory Belief. Why SCB? hypothesis; Introduction The two-system hypothesis states there are two reasoning systems (or at least two kinds of reasoning systems), the first of which (System 1 or ‘S1’) is evolutionarily old, heuristically (or associatively) based, automatic, fast, and is a collection of independent systems. The second (System 2 or ‘S2’) is evolutionarily new, perhaps peculiar to humans, is rule-based, controlled, and slow. 1 The advocate of the two-system hypothesis must demonstrate that the two systems are distinct (what I call the distinctness claim), that the two systems are of different kinds (what I call the kind claim), and that S2 is a single system. Advocates of the two- system hypothesis (I have in mind Evans (2004); Evans & Over (1996); Sloman (1993, 1996); Stanovich (1999, 2004); Carruthers (2009); and Frankish (2004, 2009)) generally support their claim by an inference to the best explanation: two systems are needed to explain experimental data from the reasoning, heuristics, and biases literature. The best evidence for this claim comes from simultaneous Contradictory Belief (henceforth SCB) (Sloman 1996, 2002). However, their inference to the best explanation only supports, if successful, the distinctness claim. While For a complete list of the property clusters of S1 and S2, sometimes called the ‘Standard Menu’, see Evans and Frankish (2009). I take the two-system hypothesis to be stronger than the existential claim that there are two systems of reasoning. The thesis is that cognition is divided into two systems and that each system has a certain set of properties associated with it—the properties on the Standard Menu. Before examining Sloman’s cases of SCB we need to understand why SCB is good evidence for the two-system hypothesis, and we need to understand what counts as evidence for SCB. Sloman seems to have a rival explanation in mind to account for human reasoning: there is just one reasoning system (call this the one-system hypothesis). The one-system hypothesis can and should allow that this system operates differently under different circumstances. It should, for example, sometimes operate deductively and other times inductively. The two-system theorist allows for a single system to operate inductively and deductive on different occasions, since S1 and S2 engage in both forms of reasoning. What, we should ask, would be the empirical difference between there being one reasoning system that operates differently under different stimuli and there being multiple systems? One reasoning system cannot have Contradictory outputs for one input (Here I am in agreement with Sloman (1996, 2002)). So the one-system hypothesis is committed to the following claim: for any question demanding reasoning and for which a reasoning system will produce only one answer, subjects will only offer one answer at any given time. Sloman understands ‘Belief’ broadly to mean “a propensity, feeling, or conviction that a response is appropriate even if it is not strong enough to be acted on” (384). This definition is not uncontroversial, but (for the sake of argument) I will grant it for the purpose of this paper. From Sloman’s definition it follows that there are at least two ways in which subjects might offer more than one response at any given time. The first is behavioral. While people might explicitly say that they believe that p, they may exhibit behavior demonstrating that they believe not-p. This would be evidence that there is more than one system involved in reasoning. They believe (explicitly) that p but believe (dispositionally, tacitly, or implicitly) not-p. Second, a subject might feel a tension between p and not-p. This is phenomenological evidence for SCB. As an example of a task where subjects give simultaneous Contradictory responses which indicates the existence of distinct systems, consider the Muller-Lyer illusion. Subjects believe that the two lines are equal, but cannot help but see them as different lengths, even after they have measured the

  • simultaneous Contradictory Belief and the two systems hypothesis
    Cognitive Science, 2013
    Co-Authors: Joshua Mugg
    Abstract:

    Simultaneous Contradictory Belief and the Two-System Hypothesis Joshua Mugg (joshuamugg@gmail.com) Department of Philosophy, 4700 Keele St. Toronto, ON M3J 1P3 Canada criticism of the two-system hypothesis has focused on the kind claim (Samuels 2009; Evans 2011), I argue that Sloman has not provided us with cases of SCB. I then offer an experimental setup that would strongly support the existence of SBC. Abstract The two-system hypothesis states that there are two kinds of reasoning systems, the first of which is evolutionarily old, heuristically (or associatively) based, automatic, fast, and is a collection of independent systems. The second is evolutionarily new, perhaps peculiar to humans, is rule-based, controlled, slow, and is a single token system. Advocates of the two-system hypothesis generally support their claim by an inference to the best explanation: two systems are needed to explain experimental data from the reasoning, heuristics, and biases literature. The best evidence for this claim comes from simultaneous Contradictory Belief (henceforth SCB) (Sloman 1996, 2002). I argue that Sloman has not provided us with cases of SCB. In each of his examples there is no evidence that the Beliefs are held simultaneously. I then offer the outline for an experimental setup that would offer compelling evidence for the existence of SCB and thereby support the two-system hypothesis. Keywords: Dual-process; two-system simultaneous Contradictory Belief. Why SCB? hypothesis; Introduction The two-system hypothesis states there are two reasoning systems (or at least two kinds of reasoning systems), the first of which (System 1 or ‘S1’) is evolutionarily old, heuristically (or associatively) based, automatic, fast, and is a collection of independent systems. The second (System 2 or ‘S2’) is evolutionarily new, perhaps peculiar to humans, is rule-based, controlled, and slow. 1 The advocate of the two-system hypothesis must demonstrate that the two systems are distinct (what I call the distinctness claim), that the two systems are of different kinds (what I call the kind claim), and that S2 is a single system. Advocates of the two- system hypothesis (I have in mind Evans (2004); Evans & Over (1996); Sloman (1993, 1996); Stanovich (1999, 2004); Carruthers (2009); and Frankish (2004, 2009)) generally support their claim by an inference to the best explanation: two systems are needed to explain experimental data from the reasoning, heuristics, and biases literature. The best evidence for this claim comes from simultaneous Contradictory Belief (henceforth SCB) (Sloman 1996, 2002). However, their inference to the best explanation only supports, if successful, the distinctness claim. While For a complete list of the property clusters of S1 and S2, sometimes called the ‘Standard Menu’, see Evans and Frankish (2009). I take the two-system hypothesis to be stronger than the existential claim that there are two systems of reasoning. The thesis is that cognition is divided into two systems and that each system has a certain set of properties associated with it—the properties on the Standard Menu. Before examining Sloman’s cases of SCB we need to understand why SCB is good evidence for the two-system hypothesis, and we need to understand what counts as evidence for SCB. Sloman seems to have a rival explanation in mind to account for human reasoning: there is just one reasoning system (call this the one-system hypothesis). The one-system hypothesis can and should allow that this system operates differently under different circumstances. It should, for example, sometimes operate deductively and other times inductively. The two-system theorist allows for a single system to operate inductively and deductive on different occasions, since S1 and S2 engage in both forms of reasoning. What, we should ask, would be the empirical difference between there being one reasoning system that operates differently under different stimuli and there being multiple systems? One reasoning system cannot have Contradictory outputs for one input (Here I am in agreement with Sloman (1996, 2002)). So the one-system hypothesis is committed to the following claim: for any question demanding reasoning and for which a reasoning system will produce only one answer, subjects will only offer one answer at any given time. Sloman understands ‘Belief’ broadly to mean “a propensity, feeling, or conviction that a response is appropriate even if it is not strong enough to be acted on” (384). This definition is not uncontroversial, but (for the sake of argument) I will grant it for the purpose of this paper. From Sloman’s definition it follows that there are at least two ways in which subjects might offer more than one response at any given time. The first is behavioral. While people might explicitly say that they believe that p, they may exhibit behavior demonstrating that they believe not-p. This would be evidence that there is more than one system involved in reasoning. They believe (explicitly) that p but believe (dispositionally, tacitly, or implicitly) not-p. Second, a subject might feel a tension between p and not-p. This is phenomenological evidence for SCB. As an example of a task where subjects give simultaneous Contradictory responses which indicates the existence of distinct systems, consider the Muller-Lyer illusion. Subjects believe that the two lines are equal, but cannot help but see them as different lengths, even after they have measured the

Julien Rossit - One of the best experts on this subject based on the ideXlab platform.

  • A max-based merging of incommensurable ranked Belief bases based on finite scales
    2007 10th International Conference on Information Fusion, 2007
    Co-Authors: Salem Benferhat, Sylvain Lagrue, Julien Rossit
    Abstract:

    Recently, several approaches have been proposed to merge possibly Contradictory Belief bases. This paper focuses on max-based merging operators applied to incommensurable ranked Belief bases. We first propose a characterization of a result of merging using Pareto-like ordering on a set of possible solutions. Then we propose two equivalent ways to recover the result of merging. The first one is based on the notion of compatible rankings defined on finite scales. The second one is only based on total pre-orders induced by ranked bases to merge.

  • FUSION - A max-based merging of incommensurable ranked Belief bases based on finite scales
    2007 10th International Conference on Information Fusion, 2007
    Co-Authors: Salem Benferhat, Sylvain Lagrue, Julien Rossit
    Abstract:

    Recently, several approaches have been proposed to merge possibly Contradictory Belief bases. This paper focuses on max-based merging operators applied to incommensurable ranked Belief bases. We first propose a characterization of a result of merging using Pareto-like ordering on a set of possible solutions. Then we propose two equivalent ways to recover the result of merging. The first one is based on the notion of compatible rankings defined on finite scales. The second one is only based on total pre-orders induced by ranked bases to merge.

Salem Benferhat - One of the best experts on this subject based on the ideXlab platform.

  • A max-based merging of incommensurable ranked Belief bases based on finite scales
    2007 10th International Conference on Information Fusion, 2007
    Co-Authors: Salem Benferhat, Sylvain Lagrue, Julien Rossit
    Abstract:

    Recently, several approaches have been proposed to merge possibly Contradictory Belief bases. This paper focuses on max-based merging operators applied to incommensurable ranked Belief bases. We first propose a characterization of a result of merging using Pareto-like ordering on a set of possible solutions. Then we propose two equivalent ways to recover the result of merging. The first one is based on the notion of compatible rankings defined on finite scales. The second one is only based on total pre-orders induced by ranked bases to merge.

  • FUSION - A max-based merging of incommensurable ranked Belief bases based on finite scales
    2007 10th International Conference on Information Fusion, 2007
    Co-Authors: Salem Benferhat, Sylvain Lagrue, Julien Rossit
    Abstract:

    Recently, several approaches have been proposed to merge possibly Contradictory Belief bases. This paper focuses on max-based merging operators applied to incommensurable ranked Belief bases. We first propose a characterization of a result of merging using Pareto-like ordering on a set of possible solutions. Then we propose two equivalent ways to recover the result of merging. The first one is based on the notion of compatible rankings defined on finite scales. The second one is only based on total pre-orders induced by ranked bases to merge.

Sylvain Lagrue - One of the best experts on this subject based on the ideXlab platform.

  • A max-based merging of incommensurable ranked Belief bases based on finite scales
    2007 10th International Conference on Information Fusion, 2007
    Co-Authors: Salem Benferhat, Sylvain Lagrue, Julien Rossit
    Abstract:

    Recently, several approaches have been proposed to merge possibly Contradictory Belief bases. This paper focuses on max-based merging operators applied to incommensurable ranked Belief bases. We first propose a characterization of a result of merging using Pareto-like ordering on a set of possible solutions. Then we propose two equivalent ways to recover the result of merging. The first one is based on the notion of compatible rankings defined on finite scales. The second one is only based on total pre-orders induced by ranked bases to merge.

  • FUSION - A max-based merging of incommensurable ranked Belief bases based on finite scales
    2007 10th International Conference on Information Fusion, 2007
    Co-Authors: Salem Benferhat, Sylvain Lagrue, Julien Rossit
    Abstract:

    Recently, several approaches have been proposed to merge possibly Contradictory Belief bases. This paper focuses on max-based merging operators applied to incommensurable ranked Belief bases. We first propose a characterization of a result of merging using Pareto-like ordering on a set of possible solutions. Then we propose two equivalent ways to recover the result of merging. The first one is based on the notion of compatible rankings defined on finite scales. The second one is only based on total pre-orders induced by ranked bases to merge.

Roderic A. Girle - One of the best experts on this subject based on the ideXlab platform.

  • Logical fiction : Real vs. ideal
    Lecture Notes in Computer Science, 1998
    Co-Authors: Roderic A. Girle
    Abstract:

    Formal systems for knowledge and Belief, from Lemmon 13 and Hintikka 11 to present day Belief Revision systems 5 , have often been described as models of ideal rational agents. From the first, there has been extensive controversy about the validity of the models. 12, 14, 18 A series of topics have given focus to the controversy. They include distinguishing knowing from believing, formalising positive and negative introspection, omniscience of various kinds, the contrast between finite and infinite, and Contradictory Belief. We consider the extent to which a range of formal models of knowledge and Belief are reasonable and realistic. We conclude with comments on the persistence of unreal models and the lack of discussion of their structure.

  • PRICAI - Logical Fiction: Real vs. Ideal
    PRICAI’98: Topics in Artificial Intelligence, 1998
    Co-Authors: Roderic A. Girle
    Abstract:

    Formal systems for knowledge and Belief, from Lemmon13 and Hintikka11 to present day Belief Revision systems5, have often been described as models of “ideal rational agents.” From the first, there has been extensive controversy about the validity of the models. 12, 14, 18 A series of topics have given focus to the controversy. They include distinguishing knowing from believing, formalising positive and negative introspection, omniscience of various kinds, the contrast between finite and infinite, and Contradictory Belief. We consider the extent to which a range of formal models of knowledge and Belief are reasonable and realistic. We conclude with comments on the persistence of unreal models and the lack of discussion of their structure.