Topics in Cognitive Science最新文献

"Is This Edible Anyway?" The Impact of Culture on the Evolution (and Devolution) of Mushroom Knowledge. “这到底能不能吃？”文化对蘑菇知识进化（和转移）的影响。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-05-26 DOI: 10.1111/tops.70011

Andrea Bender, Åge Oterhals

引用次数: 0

Open-Ended Technological Evolution: The Co-Evolution of Invention and Cognitive Technologies. 开放式技术进化：发明与认知技术的共同进化。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-05-26 DOI: 10.1111/tops.70012

Mathieu Charbonneau

{"title":"Open-Ended Technological Evolution: The Co-Evolution of Invention and Cognitive Technologies.","authors":"Mathieu Charbonneau","doi":"10.1111/tops.70012","DOIUrl":"https://doi.org/10.1111/tops.70012","url":null,"abstract":"The cumulative evolution of technology has proven central to our species' ecological success, allowing for cultural rather than biological adaptation to environmental challenges. While cumulative improvement explains how specific technological traditions can get increasingly better at solving pre-existing adaptive problems, it remains fundamentally an optimization process, one which halts when an optimal solution is found. Yet, humans are also capable of open-ended or evolvable technological change, that is, we have the capacity for generating novel and useful technological solutions for an ever-expanding set of increasingly complex problems. How novel problems of increasing complexity are accessed, however, remains an open issue. Here, I argue that human open-ended technological evolution emerges from the cultural evolutionary bootstrapping of our inventive capabilities through cognitive technologies. By inventing technologies that enhance our cognitive capabilities, we become able to invent technologies that would have been impossible to design using only our core (noncultural) cognitive abilities. These inventions include further empowering cognitive technologies, creating a feedback loop through which inventors become increasingly capable of making themselves even more capable inventors. I propose a model for how the cultural evolution of increasingly sophisticated cognitive technologies enables access to previously unreachable invention problems, driving open-ended technological change. This process differs from cumulative optimization as it involves expanding the range of problems that can be solved (evolvability) rather than optimizing solutions to existing problems (adaptation). This paper contributes to our understanding of human technological uniqueness by identifying a mechanism enabling open-ended cultural evolution.","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Knowledge Spillover, Trust, Effort, and Error Exposure in Peer-Assisted Learning. 同伴辅助学习中的知识溢出、信任、努力与错误暴露。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-05-20 DOI: 10.1111/tops.70009

Ion Juvina, Jarean Carson, Preston Menke, Peter Crowe, Chi Hang Wong, Hannah McNett

{"title":"Knowledge Spillover, Trust, Effort, and Error Exposure in Peer-Assisted Learning.","authors":"Ion Juvina, Jarean Carson, Preston Menke, Peter Crowe, Chi Hang Wong, Hannah McNett","doi":"10.1111/tops.70009","DOIUrl":"https://doi.org/10.1111/tops.70009","url":null,"abstract":"Peer-assisted learning has the potential to improve learning in academic settings and beyond. However, the cognitive and motivational mechanisms of learning through interaction with other learners are not fully understood. Here, we present an empirical study in which we compare a peer-assisted learning condition with two individual learning conditions. The empirical findings suggest that both positive and negative peer effects occurred. On the positive side, learners placed in a peer-assisted learning condition allocated more time to practice and they benefited from selectively interacting with the more knowledgeable peers. On the negative side, error exposure and increased cognitive load may have hindered learning in the peer-assisted learning condition. A computational cognitive model developed in the ACT-R cognitive architecture is presented and used to explain the mechanisms of knowledge spillover, trust, and error exposure. This research has implications for designing collaborative learning protocols to increase human collective intelligence and designing artificial intelligence systems that can support human-machine teaming.","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144112331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parallel Architecture: From Problems and Mysteries to Solutions and Explanations. 并行架构：从问题和谜团到解决方案和解释。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-05-20 DOI: 10.1111/tops.70010

Peter W Culicover, Giuseppe Varaschin

引用次数: 0

Living in the Mycelial World: A global cross-cultural ethnomycological review. 生活在菌丝世界：全球跨文化人种学回顾。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-04-30 DOI: 10.1111/tops.70003

Roope O Kaaronen

引用次数: 0

Time Tools. 时间的工具。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-04-29 DOI: 10.1111/tops.70005

Kensy Cooperrider

引用次数: 0

Cosmovision as Cognitive Technology: The Case of Mesoamerican Medicinal Knowledge. 作为认知技术的宇宙观：以中美洲医学知识为例。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-04-28 DOI: 10.1111/tops.70008

Johan De Smedt, Helen De Cruz

引用次数: 0

COHUMAIN: Building the Socio-Cognitive Architecture of Collective Human-Machine Intelligence. 构建集体人机智能的社会认知架构。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-04-01 Epub Date: 2023-06-18 DOI: 10.1111/tops.12673

Cleotilde Gonzalez, Henny Admoni, Scott Brown, Anita Williams Woolley

{"title":"COHUMAIN: Building the Socio-Cognitive Architecture of Collective Human-Machine Intelligence.","authors":"Cleotilde Gonzalez, Henny Admoni, Scott Brown, Anita Williams Woolley","doi":"10.1111/tops.12673","DOIUrl":"10.1111/tops.12673","url":null,"abstract":"In recent years, we have experienced rapid development of advanced technology, machine learning, and artificial intelligence (AI), intended to interact with and augment the abilities of humans in practically every area of life. With the rapid growth of new capabilities, such as those enabled by generative AI (e.g., ChatGPT), AI is increasingly at the center of human communication and collaboration, resulting in a growing recognition of the need to understand how humans and AI can integrate their inputs in collaborative teams. However, there are many unanswered questions regarding how human-AI collective intelligence will emerge and what the barriers might be. Truly integrated collaboration between humans and intelligent agents may result in a different way of working that looks nothing like what we know now, and it is important to keep the essential goal of human societal well-being and prosperity a priority. In this special issue, we begin to scope out the underpinnings of a socio-cognitive architecture for Collective HUman-MAchine INtelligence (COHUMAIN), which is the study of the capability of an integrated human and machine (i.e., intelligent technology) system to achieve goals in a wide range of environments. This topic consists of nine papers including a description of the conceptual foundation for a socio-cognitive architecture for COHUMAIN, empirical tests of some aspects of this architecture, research on proposed representations of intelligent agents that can jointly interact with humans, empirical tests of human-human and human-machine interactions, and philosophical and ethical issues to consider as we develop these systems.","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"180-188"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9661585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adversarial Dynamics in Centralized Versus Decentralized Intelligent Systems. 集中与分散智能系统中的对抗动力学。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-04-01 Epub Date: 2023-10-30 DOI: 10.1111/tops.12705

Levin Brinkmann, Manuel Cebrian, Niccolò Pescetelli

{"title":"Adversarial Dynamics in Centralized Versus Decentralized Intelligent Systems.","authors":"Levin Brinkmann, Manuel Cebrian, Niccolò Pescetelli","doi":"10.1111/tops.12705","DOIUrl":"10.1111/tops.12705","url":null,"abstract":"Artificial intelligence (AI) is often used to predict human behavior, thus potentially posing limitations to individuals' and collectives' freedom to act. AI's most controversial and contested applications range from targeted advertisements to crime prevention, including the suppression of civil disorder. Scholars and civil society watchdogs are discussing the oppressive dangers of AI being used by centralized institutions, like governments or private corporations. Some suggest that AI gives asymmetrical power to governments, compared to their citizens. On the other hand, civil protests often rely on distributed networks of activists without centralized leadership or planning. Civil protests create an adversarial tension between centralized and decentralized intelligence, opening the question of how distributed human networks can collectively adapt and outperform a hostile centralized AI trying to anticipate and control their activities. This paper leverages multi-agent reinforcement learning to simulate dynamics within a human-machine hybrid society. We ask how decentralized intelligent agents can collectively adapt when competing with a centralized predictive algorithm, wherein prediction involves suppressing coordination. In particular, we investigate an adversarial game between a collective of individual learners and a central predictive algorithm, each trained through deep Q-learning. We compare different predictive architectures and showcase conditions in which the adversarial nature of this dynamic pushes each intelligence to increase its behavioral complexity to outperform its counterpart. We further show that a shared predictive algorithm drives decentralized agents to align their behavior. This work sheds light on the totalitarian danger posed by AI and provides evidence that decentrally organized humans can overcome its risks by developing increasingly complex coordination strategies.","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"374-391"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12093910/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cognitive Models for Machine Theory of Mind. 机器心智理论的认知模型。

IF 2.9 2区心理学

Topics in Cognitive Science Pub Date : 2025-04-01 Epub Date: 2024-12-01 DOI: 10.1111/tops.12773

Christian Lebiere, Peter Pirolli, Matthew Johnson, Michael Martin, Donald Morrison

{"title":"Cognitive Models for Machine Theory of Mind.","authors":"Christian Lebiere, Peter Pirolli, Matthew Johnson, Michael Martin, Donald Morrison","doi":"10.1111/tops.12773","DOIUrl":"10.1111/tops.12773","url":null,"abstract":"Some of the required characteristics for a true machine theory of mind (MToM) include the ability to (1) reproduce the full diversity of human thought and behavior, (2) develop a personalized model of an individual with very limited data, and (3) provide an explanation for behavioral predictions grounded in the cognitive processes of the individual. We propose that a certain class of cognitive models provide an approach that is well suited to meeting those requirements. Being grounded in a mechanistic framework like a cognitive architecture such as ACT-R naturally fulfills the third requirement by mapping behavior to cognitive mechanisms. Exploiting a modeling paradigm such as instance-based learning accounts for the first requirement by reflecting variations in individual experience into a diversity of behavior. Mechanisms such as knowledge tracing and model tracing allow a specific run of the cognitive model to be aligned with a given individual behavior trace, fulfilling the second requirement. We illustrate these principles with a cognitive model of decision-making in a search and rescue task in the Minecraft simulation environment. We demonstrate that cognitive models personalized to individual human players can provide the MToM capability to optimize artificial intelligence agents by diagnosing the underlying causes of observed human behavior, projecting the future effects of potential interventions, and managing the adaptive process of shaping human behavior. Examples of the inputs provided by such analytic cognitive agents include predictions of cognitive load, probability of error, estimates of player self-efficacy, and trust calibration. Finally, we discuss implications for future research and applications to collective human-machine intelligence.","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"268-290"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12093916/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142773728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0