کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6853496 | 659007 | 2015 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A cognitive model fleshes out Kahneman's fast and slow systems
ترجمه فارسی عنوان
یک مدل شناختی از سیستم های سریع و آهنی کاننان است
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Daniel Kahneman (2011) posits two main processes that characterize thinking: “System 1” is a fast decision making system responsible for intuitive decision making based on emotions, vivid imagery, and associative memory. “System 2” is a slow system that observes System 1's outputs, and intervenes when “intuition” is insufficient. Such an intervention occurs “when an event is detected that violates the model of the world that System 1 maintains” (Kahneman, 2011, p. 24). Here, we propose specific underlying mechanisms for Kahneman's Systems 1 and 2, in terms of the LIDA model, a broad, systems-level, cognitive architecture (Franklin et al., 2014). LIDA postulates that human cognition consists of a continuing, overlapping iteration of cognitive cycles, each a cognitive “atom,” out of which higher-order processes are built. In LIDA terms, System 1 employs consciously mediated action selection in which a stimulus is acted upon within one or two cognitive cycles. In contrast, System 2, which LIDA posits to operate according to James' ideomotor theory (James, 1950), requires more cognitive cycles in its deliberative decision making. Thus, we suggest that System 2 employs multiple occurrences of System 1 in its operation. To test the proposed mechanisms, we perform an in silico experiment using a LIDA-based software agent.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biologically Inspired Cognitive Architectures - Volume 11, January 2015, Pages 38-52
Journal: Biologically Inspired Cognitive Architectures - Volume 11, January 2015, Pages 38-52
نویسندگان
Usef Faghihi, Clayton Estey, Ryan McCall, Stan Franklin,