The term conceptual simulation refers to a type of everyday reasoning strategy commonly called “what if” reasoning. It has been suggested in a number of contexts that this type of reasoning plays an important role in scientific discovery; however, little direct evidence exists to support this claim. This article proposes that conceptual simulation is likely to be used in situations of informational uncertainty, and may be used to help scientists resolve that uncertainty. We conducted two studies to investigate the relationship (...) between conceptual simulation and informational uncertainty. Study 1 was an in vivo study of expert scientists; the results suggest that scientists do use conceptual simulation in situations of informational uncertainty, and that they use conceptual simulation to make inferences from their data using the analogical reasoning process of alignment by similarity detection. Study 2 experimentally manipulated experts' level of uncertainty and provides further support for the hypothesis that conceptual simulation is more likely to be used in situations of informational uncertainty. Finally, we discuss the relationship between conceptual simulation and other types of reasoning using qualitative mental models. (shrink)

Blanchette and Dunbar have claimed that when participants are allowed to draw on their own source analogs in the service of analogical argumentation, retrieval is less constrained by surface similarity than traditional experiments suggest. In two studies, we adapted this production paradigm to control for the potentially distorting effects of analogy fabrication and uneven availability of close and distant sources in memory. Experiment 1 assessed whether participants were reminded of central episodes from popular movies while generating analogies for superficially similar (...) versus superficially dissimilar target situations. In Experiment 2, we modified this procedure to assess the retrieval of autobiographic memories, more familiar to participants than fictional episodes. Both studies revealed a strong effect of surface similarity on the retrieval of participants' own sources, thus suggesting that the superficial bias typically observed in experimental studies—and simulated by most computational models—does not originate in a lack of ecological validity. (shrink)

In adversarial problem solving (APS), one must anticipate, understand and counteract the actions of an opponent. Military strategy, business, and game playing all require an agent to construct a model of an opponent that includes the opponent's model of the agent. The cognitive mechanisms required for such modeling include deduction, analogy, inductive generalization, and the formation and evaluation of explanatory hypotheses. Explanatory coherence theory captures part of what is involved in APS, particularly in cases involving deception.

At a recent rally, Donald Trump resumed a habit he had developed during his election-rallies and read out the lyrics to a song. It tells the Aesopian fable of The Farmer and the Snake: A half frozen snake is taken in by a kind-hearted person but bites them the moment it is revived. Trump tells the fable to make a point about Islamic immigrants and undocumented immigrants from Southern and Central America: He claims the immigrants will cause problems and much (...) stricter immigration-policies are needed. I assume that Trump treats the fable as an argumentative device for supporting his stance on immigration. He uses it as a source-analogue both for the conclusion that immigrants will cause problems and for changing the frame in which immigrants and those willing to let them enter are seen. This gives me opportunity to examine the effect fables have as argumentative devices. Fables are a popular and effective choice for political argumentation. They are slimmed down, semi-abstract narratives, well suited for directing the audience's attention to a few properties of an otherwise complex situation. However, this also makes it easy to use them for manipulating an audience into oversimplifying complex contexts and stereotyping human beings. (shrink)

A number of theoretical positions in psychology—including variants of case‐based reasoning, instance‐based analogy, and connectionist models—maintain that abstract rules are not involved in human reasoning, or at best play a minor role. Other views hold that the use of abstract rules is a core aspect of human reasoning. We propose eight criteria for determining whether or not people use abstract rules in reasoning, and examine evidence relevant to each criterion for several rule systems. We argue that there is substantial evidence (...) that several different inferential rules, including modus ponens, contractual rules, causal rules, and the law of large numbers, are used in solving everyday problems. We discuss the implications for various theoretical positions and consider hybrid mechanisms that combine aspects of instance and rule models. (shrink)

We discuss several aspects of legal arguments, primarily arguments about the meaning of statutes. First, we discuss how the requirements of argument guide the specification and selection of supporting cases and how an existing case base influences argument formation. Second, we present,our evolving taxonomy of patterns of actual legal argument. This taxonomy builds upon our much earlier work on argument moves and also on our more recent analysis of how cases are used to support arguments for the interpretation of legal (...) statutes. Third, we show how the theory of argument used by CABARET, a hybrid case-based/rule-based reasoner, can support many of the argument patterns in our taxonomy. (shrink)

Detecting that two images are different is faster for highly dissimilar images than for highly similar images. Paradoxically, we showed that the reverse occurs when people are asked to describe how two images differ—that is, to state a difference between two images. Following structure-mapping theory, we propose that this disassociation arises from the multistage nature of the comparison process. Detecting that two images are different can be done in the initial (local-matching) stage, but only for pairs with low overlap; thus, (...) “different” responses are faster for low-similarity than for high-similarity pairs. In contrast, identifying a specific difference generally requires a full structural alignment of the two images, and this alignment process is faster for high-similarity pairs. We described four experiments that demonstrate this dissociation and show that the results can be simulated using the Structure-Mapping Engine. These results pose a significant challenge for nonstructural accounts of similarity comparison and suggest that structural alignment processes play a significant role in visual comparison. (shrink)

Given a 4-tuple of Boolean variables (a, b, c, d), logical proportions are modeled by a pair of equivalences relating similarity indicators ( \({a \wedge b}\) and \({\overline{a} \wedge \overline{b}}\) ), or dissimilarity indicators ( \({a \wedge \overline{b}}\) and \({\overline{a} \wedge b}\) ) pertaining to the pair (a, b), to the ones associated with the pair (c, d). There are 120 semantically distinct logical proportions. One of them models the analogical proportion which corresponds to a statement of the form “a (...) is to b as c is to d”. The paper inventories the whole set of logical proportions by dividing it into five subfamilies according to what they express, and then identifies the proportions that satisfy noticeable properties such as full identity (the pair of equivalences defining the proportion hold as true for the 4-tuple (a, a, a, a)), symmetry (if the proportion holds for (a, b, c, d), it also holds for (c, d, a, b)), or code independency (if the proportion holds for (a, b, c, d), it also holds for their negations \({{(\overline{a},\overline{b}, \overline{c}, \overline{d})}}\) ). It appears that only four proportions (including analogical proportion) are homogeneous in the sense that they use only one type of indicator (either similarity or dissimilarity) in their definition. Due to their specific patterns, they have a particular cognitive appeal, and as such are studied in greater details. Finally, the paper provides a discussion of the other existing works on analogical proportions. (shrink)

Cognitive Science, Volume 46, Issue 3, March 2022.

Despite its strengths, Leech et al.'s model fails to address the important benefits that derive from self-explanation and task feedback in analogical reasoning development. These components encourage explicit, self-reflective processes that do not necessarily link to knowledge accretion. We wonder, therefore, what mechanisms can be included within a connectionist framework to model self-reflective involvement and its beneficial consequences.

Speaking: from Intention to Articulation Willem J. M. Levelt, 1989 (1993 paperback) Cambridge, MA: MIT Press ISBN: 0–262–12137–9(hb), 0–262–62089–8(pb)Rules for Reasoning Richard E. Nisbett (Ed.), 1993 Hillsdale, NJ, Lawrence Erlbaum Associates ISBN: 0–8058–1256–3(hb), 0–8085–1257–1 (pb)Readings in Philosophy and Cognitive Science Alvin I. Goldman, 1993 Cambridge, MA, MIT Press ISBN: 0–262–07153–3(hb), 0–262–57100–5(pb)Language Comprehension in Ape and Child, Monographs of the Society for Research in Child Development, Serial No. 233, Vol. 58, Nos 3–4 Sue Savage‐Rumbaugh, Jeannine Murphy, Rose A. Sevcik, Karen E. (...) Brakke, Shelly L. Williams & Duane M. Rumbaugh, with commentary by Elizabeth Bates, and a reply by the authors, 1993 Chicago: University of Chicago Press ISBN: 0–226–73542–7Language, Music and Mind Diana Raffman, 1993 Cambridge, MIT Press/Bradford Books ISBN: 0–262–18150–9Psychology of Proof Lance J. Rips, 1994 Cambridge, MA, MIT Press ISBN: 0–262–18153–3Human and Machine Thinking P. Johnson‐Laird, 1993 Hillsdale, NJ, Erlbaum ISBN: 0–8058–0921‐XIntelligent Behavior in Animals and Robots David McFarland & Thomas Bosser, 1993 Cambridge, MA and London, UK: MIT Press/ Bradford Books ISBN: 0–262–13293–1The Eye and the Mind: Reflections on Perception and the Problem of Knowledge Charles Landesman, 1993 Dordrecht: Kluwer Academic Publishers ISBN: 0–7923–2586–9The Moral Self GilG. Noam & Thomas E. Wren (Eds), in cooperation with Gertud Nunner‐Winkler & Wolfgang Edelstein, 1993 Cambridge, MA: MIT Press ISBN: 0–262–14052–1The Logic of Discovery: A Theory of the Rationality of Scientific Research Scott A. Kleiner, 1993 Dordrecht: Kluwer Academic Publishers ISBN: 0–7923–2371–8Folk Psychology and the Philosophy of Mind S.M. Christenson & D.R. Turner (Eds), 1993 Hillsdale, NJ: Lawrence Erlbaum ISBN: 0–805–80931–7. (shrink)

Part 1 of this paper1 used the notions of equivocality and uncertainty to distinguish the situations in which managers make judgements and decisions and described in general how managers use models in these different contexts. This final second part describes in detail the three types of models managers use: formal models, stories and metaphors. It offers five propositions about how managers use the three types of model, propositions which can usefully form the basis of future empirical research.

The fundamental relations that underlie cognitive comparisons—“same” and “different”—can be defined at multiple levels of abstraction, which vary in relational complexity. We compared response times to decide whether or not two sequentially‐presented patterns, each composed of two pairs of colored squares, were the same at three levels of abstraction: perceptual, relational, and system (higher order relations). For both 150 ms and 5 s inter‐stimulus intervals (ISIs), both with and without a masking stimulus, decision time increased with level of abstraction. Sameness (...) at lower complexity levels contributed to decisions based on the higher levels. The pattern of comparison times across levelswas not predictable solely from encoding times. The results indicated that relations at multiple levels of complexity can be abstracted and compared in working memory, with higher complexity levels requiring more processing time. We simulated the impact of relational complexity on response time using Learning and Inference with Schemas and Analogies (LISA), a computational model of relational comparisons based on dynamic binding of elements into roles in a relational working memory. (shrink)