在 S1/S2 认知架构中使用基于三元组的方法存储和检索目标导向计划

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cognitive Systems Research Pub Date : 2024-06-18 DOI:10.1016/j.cogsys.2024.101257
Massimo Cossentino, Giovanni Pilato
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引用次数: 0

摘要

最近几年,心理学家丹尼尔-卡尼曼(Daniel Kahneman)提出的 "系统 1/系统 2 "认知结构引起了该领域许多研究人员的兴趣。系统 1 是一个直觉的、自动的、快速思考的系统,不需要有意识的努力就能毫不费力地工作。系统 2 是一个深思熟虑、善于分析、思维速度较慢的系统,需要有意识的努力和注意力。这项工作提出了一种创新方法,利用典型的信息检索技术(三元组数据结构),在系统 2 和系统 1 之间有效地编码解决方案库。该资源库存储了代理已使用过的解决方案(成功计划),并可重新执行以实现目标。系统 2 构想新计划,并委托系统 1 执行。如果计划成功(因此成为解决方案),系统 1 就会将其存储到存储库中,以便在未来快速检索任何可能有助于实现系统 2 审议的目标的解决方案。
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Using a trie-based approach for storage and retrieval of goal-oriented plans in an S1/S2 cognitive architecture

In the last years, the System 1/System 2 cognitive architecture, proposed by psychologist Daniel Kahneman, raised the interest of many researchers in the field. System 1 is an intuitive, automatic, and fast-thinking system working effortlessly, without conscious effort. System 2 is a deliberate, analytical, and slower-thinking system employing conscious effort and attention. This work proposes an innovative approach that exploits techniques typical of information retrieval (the trie data structure) to efficiently encode the solutions’ repository at the border between System 2 and System 1. This repository stores the solutions (successful plans) the agent has already used and can re-enact to achieve the goals. System 2 conceives new plans and delegates System 1 to execute them. If the plan is successful (and so it becomes a solution), System 1 stores that in the repository to quickly retrieve any solution that may help fulfil the goals deliberated by System 2 in the future.

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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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