21 papers · ranked by Valyu relevance
Armel Zebaze, Benoît Sagot, Rachel Bawden
compositionality Authors: ['Armel Zebaze' 'Benoît Sagot' 'Rachel Bawden'] Large Language Models (LLMs) have demonstrated remarkable performance across multiple tasks through in-context learning. For complex reasoning tasks that require step-by-step thinking, Chain-of-Thought (CoT) prompting has given impressive…
Margarida Romero, George Kalmpourtzis
Metacognition is an important aspect in creative problem solving (CPS) and through this chapter we analyse the meta-reasoning aspects applied in the different processes of monitoring the progress of learners' reasoning and CPS activities. Meta-reasoning monitors the way that problem-solving processes advance and…
Qianli Yang, Zhihua Zhu, Ruoguang Si, Yunwei Li + 2 more
Human intelligence is characterized by our remarkable ability to solve complex problems. This involves planning a sequence of actions that leads us from an initial state to a desired goal state. Quantifying and comparing problem-solving capabilities across species and finding its evolutional roots is a fundamental…
Jonas Schäfer, Timo Reuter, Miriam Leuchter
Spatial skills are essential cognitive abilities that develop during middle childhood and play a crucial role in solving STEM problems. In this relation, however, important aspects of problem-solving performance remain underexplored. Consequently, this study investigated whether spatial skills contribute to solution…
Katarzyna Bobrowicz, Jean-Pierre Thibaut
Flexible problem solving, the ability to deal with currently goal-irrelevant information that may have been goal-relevant in previous, similar situations, plays a prominent role in cognitive development and has been repeatedly investigated in developmental research. However, this research, spanning from infancy to the…
Mattia Eluchans, Gian Luca Lancia, Antonella Maselli, Marco D’Alessando + 2 more
We humans are capable of solving challenging planning problems, but the range of adaptive strategies that we use to address them are not yet fully characterized. Here, we designed a series of problem-solving tasks that require planning at different depths. After systematically comparing the performance of participants…
Jonas Schäfer, Timo Reuter, Miriam Leuchter, Julia Karbach + 1 more
'Adel Tekari'] Problem-solving is an important skill that is associated with reasoning abilities, action control and academic success. Nevertheless, empirical evidence on cognitive correlates of problem-solving performance in childhood is limited. Appropriate assessment tools are scarce and existing analog tasks…
Maxi Becker, Simon Davis, Roberto Cabeza
Solving a problem requires relating the pieces of information available to each other and to the solution. We investigated how the strength of these relationships determines the likelihood of solving insight tasks based on remote associates. In these tasks, the solver is provided with several cues (e.g., drop, coat…
Tarun Khajuria, Kadi Tulver, Jaan Aru
Human vision is not merely a passive process of interpreting sensory input but can also function as a problem-solving process incorporating generative mechanisms to interpret ambiguous or noisy data. This synergy between the generative and discriminative components, often described as analysis-by-synthesis, enables…
Juan Pablo Franco, Peter Bossaerts, Carsten Murawski
Many everyday tasks require people to solve computationally complex problems. However, little is known about the effects of computational hardness on the neural processes associated with solving such problems. Here, we draw on computational complexity theory to address this issue. We performed an experiment in which…
Ruiqi He, Carlos G. Correa, Thomas L. Griffiths, Mark K. Ho
How are people able to plan so efficiently despite limited cognitive resources? We aimed to answer this question by extending an existing model of human task decomposition that can explain a wide range of simple planning problems by adding structure information to the task to facilitate planning in more complex tasks.…
Linas Nasvytis, Judith E. Fan
Many problems seem to require a flash of insight to solve. What form do these sudden insights take, and what impact do they have on how people approach similar problems in the future? In this work, we prompted participants (N = 189) to think aloud as they attempted to solve a sequence of five "matchstick-arithmetic"…
Maoxin Zhang, Björn Andersson, Samuel Greiff
Problem-solving is a critical aspect of intelligence that has become increasingly important in modern society. Mapping out the determinants of success in problem-solving helps understand the underlying cognitive processes involved. This article focuses on two key cognitive processes in problem-solving: non-targeted…
Reiji Ohkuma, Yuto Kurihara, Toru Takahashi, Rieko Osu
People solve insight problems that they encounter daily with a sudden sense of ‘aha!’ to reach a solution. Chunk decomposition, which decomposes the factors of the problem, and constraint relaxation, which manipulates filters to organize the information necessary to solve the problem, are important in insight…
Pizza Ka Yee Chow, Kenta Uchida, Itsuro Koizumi
Urban areas are expanding exponentially, leading more wildlife species to reside and settle in this environment. Urban environmental characteristics, such as human disturbance or green coverage, have been shown to affect some cognitive abilities such as innovative problem-solving performance of wildlife species.…
Giacomo Zamprogno, Emmanuelle Dietz, Linda Heimisch, Nele Russwinkel
Human-awareness is an ever more important requirement for AI systems that are designed to assist humans with daily physical interactions and problem solving. This is especially true for patients that need support to stay as independent as possible. To be human-aware, an AI should be able to anticipate the intentions of…
Hashmath Shaik, Alex Doboli
Implementation Generation of Solutions to Open-Ended Problems Authors: ['Hashmath Shaik' 'Alex Doboli'] Abstract—Large Language Models offer new opportunities to devise automated implementation generation methods that can tackle problem solving activities beyond traditional methods, which require algorithmic…
Juliana Gottschling, Florian Krieger, Samuel Greiff
The development of a vaccine marks a breakthrough in the fight against infectious diseases. However, to eradicate highly infectious diseases globally, the immunization of large parts of the population is needed. Otherwise, diseases, such as polio, measles, or more recently COVID-19, will repeatedly flare-up, with…
Guillaume Povéda, Ryma Boumazouza, Andreas Strahl, Mark Hall + 6 more
'Santiago Quintana-Amate' 'Nahum Álvarez' 'Ignace Bleukx' 'Dimosthenis C. Tsouros' 'Hélène Verhaeghe' 'Tias Guns'] In industrial contexts, effective workforce allocation is crucial for operational efficiency. This paper presents an ongoing project focused on developing a decision-making tool designed for workforce…
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Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…
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Inverse problems, where we seek the values of inputs to a model that lead to a desired set of outputs, are a challenges subset of problems in science and engineering. In this work we demonstrate the use of two generative AI methods to solve inverse problems. We compare this approach to two more conventional approaches…