Mental models, computational explanation and Bayesian cognitive science: commentary on Knauff and Gazzo Castañeda (2022)

2021 ◽  
pp. 1-12
Author(s):  
Mike Oaksford
Keyword(s):  
Cognitive Science ◽  
Mental Models ◽  
Computational Explanation ◽  
Bayesian Cognitive Science

David Herman, Story logic. Lincoln & London: University of Nebraska Press, 2002, Pp. xvi, 477. Hb $60.00

2003 ◽  
Vol 32 (5) ◽  
pp. 722-725
Author(s):  
Anna De Fina
Keyword(s):  
Cognitive Science ◽  
Mental Models ◽  
Narrative Theory ◽  
Language Theory ◽  
Cognitive Approach ◽  
The World ◽  
Linguistic Approaches ◽  
Narrative Understanding

One of the virtues of David Herman's Story logic lies in its attempt to bring together literary and linguistic approaches to the study of narrative. The attempt results in a synthesis that promotes a better understanding of discourse for literary scholars and a deeper grasp of basic narratology tools for discourse analysts. The title of the volume reflects one of the main points of the book: that “stories both have a logic and are logic in their own right” (p. 22) because they constitute a powerful instrument for understanding the world. The more general objective of the analyses presented in the volume is to work toward a cognitive approach to narrative in which narrative understanding is explained as a process of creating and updating mental models of particular storyworlds. Thus, Herman looks at language theory and narrative theory as theoretical frames that not only can enrich each other, but that also constitute a resource for cognitive science in general.

scholarly journals Pseudo-conditionals and causal assertibles in Stoic logic

2017 ◽  
Vol 20 (3) ◽  
pp. 417
Author(s):  
Miguel López-Astorga
Keyword(s):  
Cognitive Science ◽  
Mental Models ◽  
Semantic Analysis ◽  
Methodological Tool ◽  
Conditional Perfection ◽  
Stoic Logic ◽  
Mental Models Theory

http://dx.doi.org/ 10.5007/1808-1711.2016v20n3p417The Stoics not only analyzed sentences showing to be clear conditionals. They also reviewed other kinds of sentences related to the conditional that are not exactly conditionals, for example, the pseudo-conditionals and the causal assertibles. In this paper, I try to argue that the Stoic account of such sentences reveals that certain problematic issues that contemporary cognitive science is concerned with, such as the ways the conditionals can be expressed or the pragmatic phenomenon of the conditional perfection, were already studied by the Stoics, and that they even gave their solutions to those problems. To do that, I resort to the semantic analysis of models usually made by the mental models theory, and use it as a methodological tool.

scholarly journals The imaginary fundamentalists: The unshocking truth about Bayesian cognitive science

2011 ◽  
Vol 34 (4) ◽  
pp. 194-196 ◽  
Author(s):  
Nick Chater ◽  
Noah Goodman ◽  
Thomas L. Griffiths ◽  
Charles Kemp ◽  
Mike Oaksford ◽  
...  
Keyword(s):  
Cognitive Science ◽  
Neural Circuits ◽  
Behavioral Data ◽  
Multiple Models ◽  
Close Attention ◽  
Environmental Structure ◽  
Bayesian Cognitive Science ◽  
Future Practice

AbstractIf Bayesian Fundamentalism existed, Jones & Love's (J&L's) arguments would provide a necessary corrective. But it does not. Bayesian cognitive science is deeply concerned with characterizing algorithms and representations, and, ultimately, implementations in neural circuits; it pays close attention to environmental structure and the constraints of behavioral data, when available; and it rigorously compares multiple models, both within and across papers. J&L's recommendation of Bayesian Enlightenment corresponds to past, present, and, we hope, future practice in Bayesian cognitive science.

scholarly journals Mental Models in Cognitive Science

1980 ◽  
Vol 4 (1) ◽  
pp. 71-115 ◽  
Author(s):  
P.N. Johnson-Laird
Keyword(s):  
Cognitive Science ◽  
Mental Models

scholarly journals There Can be a Syntax of Thought Related to Logical Forms

2017 ◽  
Vol 8 (1) ◽  
pp. 270-278
Author(s):  
Miguel López-Astorga
Keyword(s):  
Cognitive Science ◽  
Mental Models ◽  
Human Mind ◽  
Axiomatic System ◽  
Science Literature ◽  
Basic Framework ◽  
The Way ◽  
Mental Models Theory

Abstract Nowadays, a very important theory, the mental models theory, is demonstrating that it is able to explain most of the results in reasoning experiments reported by the cognitive science literature. However, this has a consequence. The mental models theory is mainly focused on content and meaning, and its theses can lead to reject the idea that syntax plays a role in the human mind and that reasoning is logical. But, in this paper, I try to show that it is possible to accept the basic framework of the mental models theory and, at the same time, to continue to claim that there are syntactic and formal logical processes coherent with the way our mind works. To do that, I argue that, even accepting that the mental models theory describes correctly the processes why certain combinations of possibilities are detected, it can be stated that the relationships between such combinations indicated by the theory are consistent with, for example, the modal axiomatic system K.

scholarly journals Perception of learning in programming lectures based on mental models

2020 ◽  
pp. 41375-41377
Keyword(s):  
Cognitive Science ◽  
Mental Models ◽  
Mental Model ◽  
Technical Education ◽  
Human Mind ◽  
The Way

The understanding of the human mind and its ability to learn are objects of research in Cognitive Science. The way a person learns is unique, the result of her previous experiences and the development of her mental model. The understanding of how the students produce their mental models can favor the learning of several disciplines, as evidenced in several papers. In this context, this work investigates the combination of mental models used by students within the lecture of Programming in technical education classes. The analysis was based on a test that identifies strengths and weaknesses in the structuring of mental models.

scholarly journals Probabilistic Biases Meet the Bayesian Brain

2020 ◽  
Vol 29 (5) ◽  
pp. 506-512
Author(s):  
Nick Chater ◽  
Jian-Qiao Zhu ◽  
Jake Spicer ◽  
Joakim Sundh ◽  
Pablo León-Villagrá ◽  
...  
Keyword(s):  
Decision Making ◽  
Cognitive Science ◽  
Mental Simulation ◽  
Judgment And Decision Making ◽  
Heuristics And Biases ◽  
Bayesian Brain ◽  
Anchoring And Adjustment ◽  
The Mind ◽  
The Brain ◽  
Bayesian Cognitive Science

In Bayesian cognitive science, the mind is seen as a spectacular probabilistic-inference machine. But judgment and decision-making (JDM) researchers have spent half a century uncovering how dramatically and systematically people depart from rational norms. In this article, we outline recent research that opens up the possibility of an unexpected reconciliation. The key hypothesis is that the brain neither represents nor calculates with probabilities but approximates probabilistic calculations by drawing samples from memory or mental simulation. Sampling models diverge from perfect probabilistic calculations in ways that capture many classic JDM findings, which offers the hope of an integrated explanation of classic heuristics and biases, including availability, representativeness, and anchoring and adjustment.

Sign in / Sign up

Export Citation Format

Share Document