The mental representation of causal conditional reasoning: Mental models or causal models

Cognition ◽  
2011 ◽  
Vol 119 (3) ◽  
pp. 403-418 ◽  
Author(s):  
Nilufa Ali ◽  
Nick Chater ◽  
Mike Oaksford
Keyword(s):  
Mental Models ◽  
Mental Representation ◽  
Causal Models ◽  
Conditional Reasoning

On the Mental Representation of Conditional Sentences

1996 ◽  
Vol 49 (4) ◽  
pp. 1086-1114 ◽  
Author(s):  
Jonathan St. B. T. Evans ◽  
Charles E. Ellis ◽  
Stephen E. Newstead
Keyword(s):  
Mental Models ◽  
Research Methods ◽  
Mental Representation ◽  
Conditional Reasoning ◽  
Strong Tendency ◽  
Inference Rules ◽  
Counter Example ◽  
First Finding ◽  
Blue Triangle ◽  
Conditional Statements

Four experiments are reported which attempt to externalize subjects’ mental representation of conditional sentences, using novel research methods. In Experiment 1, subjects were shown arrays of coloured shapes and asked to rate the degree to which they appeared to be true of conditional statements such as “If the figure is green then it is a triangle”. The arrays contained different distributions of the four logically possible cases in which the antecedent or consequent is true or false: TT, TF, FT, and FF. For example, a blue triangle would be FT for the conditional quoted above. In Experiments 2 to 4, subjects were able to construct their own arrays to make conditionals either true or false with any distribution of the four cases they wished to choose. The presence and absence of negative components was varied, as was the form of the conditional, being either “if then” as above or “only if”: “The figure is green only if it is a triangle”. The first finding was that subjects represent conditionals in fuzzy way: conditionals that include some counter-example TF cases (Experiment 1) may be rated as true, and such cases are often included when subjects construct an array to make the rule true (Experiments 2 to 4). Other findings included a strong tendency to include psychologically irrelevant FT and FF cases in constructed arrays, presumably to show that conditional statements only apply some of the time. A tendency to construct cases in line with the “matching bias” reported on analogous tasks in the literature was found, but only in Experiment 4, where the number of symbols available to construct each case was controlled. The findings are discussed in relation to the major contemporary theories of conditional reasoning based upon inference rules and mental models, neither of which can account for all the results.

Causal Models and Conditional Reasoning

2017 ◽  
Author(s):  
Mike Oaksford ◽  
Nick Chater
Keyword(s):  
Model Theory ◽  
Causal Model ◽  
Recent Model ◽  
Causal Models ◽  
Conditional Reasoning ◽  
Cognitive System ◽  
Markov Condition ◽  
Bayes Nets ◽  
Causal Bayes Nets ◽  
Conditional Statements

There are deep intuitions that the meaning of conditional statements relate to probabilistic law-like dependencies. In this chapter it is argued that these intuitions can be captured by representing conditionals in causal Bayes nets (CBNs) and that this conjecture is theoretically productive. This proposal is borne out in a variety of results. First, causal considerations can provide a unified account of abstract and causal conditional reasoning. Second, a recent model (Fernbach & Erb, 2013) can be extended to the explicit causal conditional reasoning paradigm (Byrne, 1989), making some novel predictions on the way. Third, when embedded in the broader cognitive system involved in reasoning, causal model theory can provide a novel explanation for apparent violations of the Markov condition in causal conditional reasoning (Ali et al, 2011). Alternative explanations are also considered (see, Rehder, 2014a) with respect to this evidence. While further work is required, the chapter concludes that the conjecture that conditional reasoning is underpinned by representations and processes similar to CBNs is indeed a productive line of research.

scholarly journals Much ado about nothing: The mental representation of omissive relations

2020 ◽  
Author(s):  
Sangeet Khemlani ◽  
Paul Bello ◽  
Gordon Briggs ◽  
Hillary Harner ◽  
Christina Wasylyshyn
Keyword(s):  
Mental Models ◽  
Mental Representation ◽  
Model Theory ◽  
Mental Simulation ◽  
Alternative Possibilities ◽  
Temporal Relations ◽  
Causal Relations ◽  
Much Ado About Nothing ◽  
The Mind ◽  
Force Vectors

When the absence of an event causes some outcome, it is an instance of omissive causation. For instance, not eating lunch may cause you to be hungry. Recent psychological proposals concur that the mind represents causal relations, including omissive causal relations, through mental simulation, but they disagree on the form of that simulation. One theory states that people represent omissive causes as force vectors; another states that omissions are representations of contrasting counterfactual simulations; a third argues that people think about omissions by representing sets of iconic possibilities – mental models – in a piecemeal fashion. In this paper, we tease apart the empirical predictions of the three theories and describe experiments that run counter to two of them. Experiments 1 and 2 show that reasoners can infer temporal relations from omissive causes – a pattern that contravenes the force theory. Experiment 3 asked participants to list the possibilities consistent with an omissive cause – it found that they tended to list particular privileged possibilities first, most often, and faster than alternative possibilities. The pattern is consistent with the model theory, but inconsistent with the contrast hypothesis. We marshal the evidence and explain why it helps to solve a long-standing debate about how the mind represents omissions.

Reasoning with three Types of Conditional: Biases and Mental Models

1993 ◽  
Vol 46 (4) ◽  
pp. 653-677 ◽  
Author(s):  
Thomas C. Ormerod ◽  
Kenneth I. Manktelow ◽  
Gregory V. Jones
Keyword(s):  
Mental Models ◽  
Internal Structure ◽  
Temporal Order ◽  
Conditional Reasoning ◽  
Rule Generation ◽  
Differential Effects ◽  
Evaluation Task ◽  
Abstract Rule ◽  
Pattern Of Performance ◽  
Rule Evaluation

Two experiments are reported which compare conditional reasoning with three types of rule. These consist of two types of rule that have been widely studied previously, if p then q and p only if q, together with a third type, q if p. In both experiments, the p only if q type of rule yields a different pattern of performance from the two other types of rule. Experiment 1 is an abstract rule-evaluation task and demonstrates differential effects of temporal order and of suppositional bias. Experiment 2 investigates rule generation, rephrasing, and comparison, and demonstrates differential effects of temporal order and of thematic content. An analysis of the results is offered in terms of biases and mental models. Effects of rule form and context can be explained as reflecting the different sequences in which mental models are created for each rule form. However, it is necessary to consider the internal structure of individual mental models to account for effects arising from temporal ordering of rules.

Mental Models in Conditional Reasoning and Working Memory

1999 ◽  
Vol 5 (4) ◽  
pp. 289-302 ◽  
Author(s):  
Pierre Barrouillet ◽  
Jean-Francois Lecas
Keyword(s):  
Working Memory ◽  
Mental Models ◽  
Conditional Reasoning

Conditional reasoning by mental models: chronometric and developmental evidence

Cognition ◽  
2000 ◽  
Vol 75 (3) ◽  
pp. 237-266 ◽  
Author(s):  
Pierre Barrouillet ◽  
Nelly Grosset ◽  
Jean-François Lecas
Keyword(s):  
Mental Models ◽  
Conditional Reasoning

scholarly journals Discounting and Augmentation in Causal Conditional Reasoning: Causal Models or Shallow Encoding?

PLoS ONE ◽  
2016 ◽  
Vol 11 (12) ◽  
pp. e0167741 ◽  
Author(s):  
Simon Hall ◽  
Nilufa Ali ◽  
Nick Chater ◽  
Mike Oaksford
Keyword(s):  
Causal Models ◽  
Conditional Reasoning
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