United States

The current study investigates the effect of constraints in well-structured problem-solving on ill-structured problem-solving by asking people to solve variants of Raven’s advanced progressive matrices (APM) and to create an APM-like puzzle using the creative reasoning task (CRT). Using traditional APM, we created a novel version of APM with comparatively lesser constraints available to solve the puzzle, called creative APM (cAPM). The cAPM task was designed to induce divergent thinking along with convergent thinking by enabling our participants to create new rules, if possible, to complete the puzzle. It is assumed that the change in constraints or availability of rules to deduce reasoning changes the nature of the problem space in solving APM and cAPM and may differently affect the following creative reasoning task. We randomly assigned 50 participants to perform APM or the variant of the APM task, i.e. cAPM, followed by the CRT, in a fixed order. We observed a significant effect of constraints available to solve well-structured problems on ill-structured problem-solving. The current result shows higher CRT scores when CRT preceded cAPM (Median = 79.25) than APM (Median =53.00), suggesting that the lesser constraints could induce divergent thinking required for a better creative reasoning task performance.

CogSci 2023

Do constraints in APM solving affect APM-like puzzle creation?

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
- Biometrics, Human Analysis and Behavior Understanding; Computer Vision, Robotics and Intelligent Systems; 
- Document and Media Analysis; and 
- Image and Signal Processing. 

The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


ICPR 2020

poster

The 45th Annual Meeting of the Cognitive Science Society will take place in Sydney, Australia as a modified hybrid conference. Presentations from the main-session room will be live-streamed every day for all events. This will include all invited talks and award sessions. Recordings of all CogSci 2023 sessions will be made available for on-demand viewing after the conference.<br>
The in-person component will be held at the International Convention Centre Sydney at Darling Harbour. The Conference will take place Wednesday July 26th – Saturday July 29th, 2023 (Wednesday, July 26th is the Workshops Day).

Join us!

<br>[**The Program at a Glance can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2023/07/COgSci-PAAG-V2.pdf)
<br>[**The Detailed Program can be found here**](https://online.fliphtml5.com/ebtyf/mswz/)
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#### **CogSci 2023 Program Book**
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The 45th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Research on how individuals process
information in politics has provided evidence for the selective
processing of information. This has often been attributed to
“motivated reasoning” (MR) , which is targeted towards 
partisan goals as opposed to ‘rational’ reasoning, which tries 
to achieve accuracy goals. We propose that political reasoning is
asymmetrical and MR is only triggered when belief-challenging 
information is presented and not when the information is
belief-conforming (congruent).

To test these claims we performed an experiment and found
that for congruent information, the initial polarization
of the subject did not significantly influence the trust rating for
the information item. But the evaluation did affect the belief
update. In contrast, for incongruent information the polariza-
tion of the subject influenced the trust rating but there was no
significant effect of the evaluation on the belief update. The
finding is consistent with behavior that tries to reduce cogni-
tive dissonance.

Asymmetry in Political Information Processing: Congruency-based reasoning in belief revision and political decision making

The present paper reports an experiment (N = 348) with a two-year-delayed (M = 695 days) follow-up that tests an approach to raising willingness to take climate actions. Here we focus on the longitudinal results. Many Americans still do not view climate change as a threat requiring urgent action. Moreover, among U.S. conservatives, higher science literacy is paradoxically associated with higher anthropogenic climate-change skepticism. Our experimental materials were designed to harness the power of two cognitive constraints — coherence and causal invariance, which map onto two narrative proclivities that anthropologists have identified as universal — to promote climate action across the political spectrum. Towards that goal, the essential role of these constraints in belief formation predicts that climate-change information would be more persuasive when it is embedded in a personal climate-action narrative, the evocation of which can benefit from exposure to parsimonious scientific explanations of indisputable everyday observations, juxtaposed with reasoners’ own, typically less coherent explanations, occurring in a context that engages their moral stance. Our brief one-time intervention, conducted in U.S. states with the highest level of climate skepticism, showed that across the political spectrum, our materials raised willingness to take climate actions in the immediate assessment. It also raised the likelihood of reports two years later of having taken or would have taken those actions had the opportunity existed, suggesting that the effects are long-lasting. Our approach adopts the framework that conceptions of reality are representations, and adaptive solutions in that infinite space of representations require cognitive constraints to narrow the search.

Promoting Climate Actions: Applying a cognitive constraints approach

Recent years have seen a surge of interest in probabilistic measures of argument strength. Such measures have been used to elucidate longstanding questions of both theoretical and practical interest around fallacies of argumentation, scientific argument, legal argument, or argument and evidence aggregation. The measures typically used have drawn, in one form or other, on conditional probability as a central component for measuring argument quality, strength or confirmation. Work in this area has also consistently highlighted the value of Bayesian Belief Networks for computing argument strength in multi-argument (variable) contexts. However, to date, there has been no consideration of whether the key structural property underlying such networks – the notion of conditional independence- has a bearing on argument quality. In this paper, we consider the potential impact of causal structure on the utility of arguments.

Causal Structure and Argumentative Value

The investigation of reasoning involves the study of what is rational (e.g., adequate, optimal) as well as the study of human reasoning (e.g., common intuitions on plausibility). While the first aspect is typically covered by logic or formal epistemology, the second is a matter of empirical psychological research. However, many approaches relate both aspects. This paper discusses these hybrid approaches, their motivation, general critiques that have been raised against them as well as the kind of philosophical commitment behind choosing such kind of framework.


Hybrid Frameworks of Reasoning: Normative-Descriptive Interplay

Since Gottlob Frege’s disambiguation of laws of thought, logicians and psychologists alike have adhered to a strict division of labour, which has created a gap between reasoning as a psychological phenomenon and logic as a formal discipline. However, logic is a benchmark of reasoning according to the standard picture of rationality, and it is hard to accept that logic has no positive special role to play in reasoning. Intuitively, logic and reasoning are connected; however, attempts at bridging the gap are often vulnerable to accusations of psychologism. 
Jean Piaget developed a compass to navigate the hazards of psychologism, and he made logic the mirror of thought rather than vice versa. Metaphors are helpful but ultimately poor substitutes for explanations; in this paper, I therefore intend to elaborate on Piaget’s intimations on the relationship between logic and reasoning to negotiate the pitfalls of psychologism and bridge the gap in mind.

Logic and Psychology—Minding the Gap with Jean Piaget

It is common for cases where people “fail to deny” unflattering claims to be taken to imply those claims are true. Yet, the ‘argument from ignorance’ – arguing in favour of something due to a lack of evidence against it – is often deemed a fallacy. Why is abduction from missing evidence permissible in some cases but not others? We present a framework of factors which disambiguate these cases, using a Bayesian Network model. We suggest that a source’s silence often reflects a latent conflict between their intrinsic motives about what they would like their audience to believe and their extrinsic motives about complying with the institutional constraints on their speech, such as accuracy. Thus, silence often implies that the source does not believe what they would ideally like to say is true, which licenses a probabilistic inference about what is true. We present data from two studies suggesting people reason about silence in this way.

The Epistemic Weight of Silence

This study identified a novel and robust reasoning error. Lay reasoners significantly deviate from the prediction of Bayesian inference by consistently underestimating the added probative value of corroborating testimonial reports. Most surprisingly, however, is that in certain contexts the sum of corroborating evidence is considered to be significantly less valuable than a single report. There is a selective devaluing of corroborating testimony when a highly reliable report is corroborated by less reliable, but credible, reports. This intuitive error is not explained by an inaccurate understanding of individual cues of reliability and number of reports, but specifically when it is required to integrate these both cues. Findings indicate the operation of alternative reasoning strategies, resulting in errors at individual and group level.

Evaluating testimony from multiple witnesses: consistent undervaluing and selective devaluing of corroborating reports

Theories can be designed to predict novel evidence or to accommodate known evidence. Despite the lively debate in philosophy of science whether prediction may hold a superior value over accommodation, people’s intuitions about this issue have not been empirically examined. Within a medical scenario, we assess individuals’ sensitivity to this dilemma. Overall, we find tentative evidence that people favour the predictive account and regard the predicting theorist (i.e., doctor) as more reliable in contrast to the accommodating counterpart. Strikingly, discrepant preference patterns emerged out of their verbal reasoning data echoing the distinct philosophical stances surprisingly well. Possible reasons why people’s reasoning systematically diverges despite the general preference for prediction are discussed.


Do people prefer prediction over accommodation? An empirical study

Intuitive conceptual systems impact how university students learn formal biological science. One such conceptual system--anthropocentric thinking--involves anchoring our understanding of the biological world in human terms. Prior research indicates that anthropocentric thinking, like other intuitive conceptual systems, can engender misconceptions, but also varies with richness of informal biological experience. To examine the impact of informal experience on anthropocentric thinking and formal biology learning, we assessed students from a rural institution (n=212) and an urban institution (n=188) on their use of anthropocentric reasoning and their agreement with biological misconceptions using both qualitative coding of free responses and quantitative analysis of close-ended measures. Our findings indicate linkages between anthropocentric thinking and misconceptions, as well as differences between urban and rural students. This work demonstrates context-based variability in anthropocentric thinking, highlights potential mechanisms driving this variability, and underlines the implications of intuitive thinking for STEM learning.

Relations Between Anthropocentric Thinking and Biological Misconceptions in Students attending Urban and Rural Universities

We investigate people’s use of strategies for sampling data in an active learning task. In the spirit of resource-rational analysis, we argue that people may often use effective heuristics to guide sampling in lieu of more computationally expensive optimization strategies, but that they do not simply continue relying heuristics that are shown to be ineffective, but instead flexibly shift to new strategies. By clustering participants’ sampling behaviour, we show that people engage in varied sampling strategies, shifting more often when encountering some function families. Although not all strategies improved participants’ performance on a subsequent prediction task, when the function family changed, participants quickly updated their beliefs about the likely function family on subsequent trials. Although sparse opportunities to learn may limit participants’ ability to fully learn the underlying functional relationships, people’s ability to dynamically shift their active learning behaviour may help them understand the abstract features of complex relationships.

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Asymmetry in Political Information Processing: Congruency-based reasoning in belief revision and political decision making

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