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Stefan Depeweg; Contantin A. Rothkopf; Frank Jäkel – Cognitive Science, 2024
More than 50 years ago, Bongard introduced 100 visual concept learning problems as a challenge for artificial vision systems. These problems are now known as Bongard problems. Although they are well known in cognitive science and artificial intelligence, only very little progress has been made toward building systems that can solve a substantial…
Descriptors: Visual Learning, Problem Solving, Cognitive Science, Artificial Intelligence
Chan, Jenny Yun-Chen; Nagashima, Tomohiro; Closser, Avery H. – Cognitive Science, 2023
Given the recent call to strengthen collaboration between researchers and relevant practitioners, we consider participatory design as a way to advance Cognitive Science. Building on examples from the Learning Sciences and Human-Computer Interaction, we (a) explore "what," "why," "who," "when," and…
Descriptors: Cognitive Science, Learning Processes, Man Machine Systems, Cooperation
Seidenberg, Mark S.; Plaut, David C. – Cognitive Science, 2014
Rumelhart and McClelland's chapter about learning the past tense created a degree of controversy extraordinary even in the adversarial culture of modern science. It also stimulated a vast amount of research that advanced the understanding of the past tense, inflectional morphology in English and other languages, the nature of linguistic…
Descriptors: Morphemes, Morphology (Languages), Language Acquisition, Reading
Cassimatis, Nicholas L.; Bello, Paul; Langley, Pat – Cognitive Science, 2008
Computational models will play an important role in our understanding of human higher-order cognition. How can a model's contribution to this goal be evaluated? This article argues that three important aspects of a model of higher-order cognition to evaluate are (a) its ability to reason, solve problems, converse, and learn as well as people do;…
Descriptors: Artificial Intelligence, Cognitive Psychology, Thinking Skills, Computation