Modeling the Remote Associates Test as Retrievals from Semantic Memory
The Remote Associates Test (RAT) is a word association retrieval task that consists of a series of problems, each with three seemingly unrelated prompt words. The subject is asked to produce a single word that is related to all three prompt words. In this paper, we provide support for a theory in wh...
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Published in | Cognitive science Vol. 46; no. 6; pp. e13145 - n/a |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
Wiley
01.06.2022
Wiley Subscription Services, Inc John Wiley and Sons Inc |
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Online Access | Get full text |
ISSN | 0364-0213 1551-6709 1551-6709 |
DOI | 10.1111/cogs.13145 |
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Abstract | The Remote Associates Test (RAT) is a word association retrieval task that consists of a series of problems, each with three seemingly unrelated prompt words. The subject is asked to produce a single word that is related to all three prompt words. In this paper, we provide support for a theory in which the RAT assesses a person's ability to retrieve relevant word associations from long‐term memory. We present a computational model of humans solving the RAT and investigate how prior knowledge and memory retrieval mechanisms influence the model's ability to match human behavior. We expand prior modeling attempts by investigating multiple large knowledge bases and by creating a cognitive process model that uses long‐term memory spreading activation retrieval processes inspired by ACT‐R and implemented in Soar. We evaluate multiple model variants for their ability to model human problem difficulty, including the incorporation of noise and base‐level activation into memory retrieval. We conclude that the main factors affecting human difficulty are the existence of associations between prompt words and solutions, the relative strengths and directions of those associations compared to associations to other words, and the ability to perform multiple retrievals. |
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AbstractList | The Remote Associates Test (RAT) is a word association retrieval task that consists of a series of problems, each with three seemingly unrelated prompt words. The subject is asked to produce a single word that is related to all three prompt words. In this paper, we provide support for a theory in which the RAT assesses a person's ability to retrieve relevant word associations from long‐term memory. We present a computational model of humans solving the RAT and investigate how prior knowledge and memory retrieval mechanisms influence the model's ability to match human behavior. We expand prior modeling attempts by investigating multiple large knowledge bases and by creating a cognitive process model that uses long‐term memory spreading activation retrieval processes inspired by ACT‐R and implemented in Soar. We evaluate multiple model variants for their ability to model human problem difficulty, including the incorporation of noise and base‐level activation into memory retrieval. We conclude that the main factors affecting human difficulty are the existence of associations between prompt words and solutions, the relative strengths and directions of those associations compared to associations to other words, and the ability to perform multiple retrievals. The Remote Associates Test (RAT) is a word association retrieval task that consists of a series of problems, each with three seemingly unrelated prompt words. The subject is asked to produce a single word that is related to all three prompt words. In this paper, we provide support for a theory in which the RAT assesses a person's ability to retrieve relevant word associations from long-term memory. We present a computational model of humans solving the RAT and investigate how prior knowledge and memory retrieval mechanisms influence the model's ability to match human behavior. We expand prior modeling attempts by investigating multiple large knowledge bases and by creating a cognitive process model that uses long-term memory spreading activation retrieval processes inspired by ACT-R and implemented in Soar. We evaluate multiple model variants for their ability to model human problem difficulty, including the incorporation of noise and base-level activation into memory retrieval. We conclude that the main factors affecting human difficulty are the existence of associations between prompt words and solutions, the relative strengths and directions of those associations compared to associations to other words, and the ability to perform multiple retrievals.The Remote Associates Test (RAT) is a word association retrieval task that consists of a series of problems, each with three seemingly unrelated prompt words. The subject is asked to produce a single word that is related to all three prompt words. In this paper, we provide support for a theory in which the RAT assesses a person's ability to retrieve relevant word associations from long-term memory. We present a computational model of humans solving the RAT and investigate how prior knowledge and memory retrieval mechanisms influence the model's ability to match human behavior. We expand prior modeling attempts by investigating multiple large knowledge bases and by creating a cognitive process model that uses long-term memory spreading activation retrieval processes inspired by ACT-R and implemented in Soar. We evaluate multiple model variants for their ability to model human problem difficulty, including the incorporation of noise and base-level activation into memory retrieval. We conclude that the main factors affecting human difficulty are the existence of associations between prompt words and solutions, the relative strengths and directions of those associations compared to associations to other words, and the ability to perform multiple retrievals. |
Author | Laird, John E. Schatz, Jule Jones, Steven J. |
AuthorAffiliation | 1 Computer Science and Engineering Division of the Electrical Engineering and Computer Science Department University of Michigan |
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Cites_doi | 10.1002/jocb.35 10.1371/journal.pone.0248986 10.1016/j.cognition.2013.03.001 10.1002/jocb.177 10.1111/tops.12548 10.3758/s13428-018-1131-7 10.3758/s13428‐018‐1115‐7 10.1016/0010-0285(74)90021-8 10.3758/BF03195543 10.1111/tops.12146 10.3115/v1/D14-1162 10.3389/fpsyg.2017.00099 10.1037/0278-7393.10.4.791 10.1016/j.patrec.2015.05.015 10.1037/h0048850 10.1111/j.1745-3984.1971.tb00914.x 10.1037/a0036773 |
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Keywords | Cognitive architecture Cognitive modeling Semantic memory Remote Associates Test |
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SubjectTerms | Association Measures Associative Learning Cognitive ability Cognitive architecture Cognitive modeling Cognitive Processes Computation Computer applications Difficulty Level Humans Knowledge Long Term Memory Memory Memory, Long-Term Prior Learning Problem Solving Prompting Recall (Psychology) Regular Remote Associates Test Semantic memory Semantics Task Analysis |
Title | Modeling the Remote Associates Test as Retrievals from Semantic Memory |
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