TY  - JOUR
TI  - Neuronal Unit of Thoughts (NUTs); AÂ Probabilistic Formalism for Higher-Order Cognition
SP  - 855
ID  - scholars15696
N1  - cited By 1; Conference of 2nd International Conference on Communication and Intelligent Systems, ICCIS 2020 ; Conference Date: 26 December 2020 Through 27 December 2020; Conference Code:261899
N2  - A probabilistic graphical model, Neuronal Unit of Thoughts (NUTs), is proposed in this paper that offers a formalism for the integration of lower-level cognitions. Nodes or neurons in NUTs represent sensory data or mental concepts or actions, and edges the causal relation between them. A node affects a change in the Action Potential (AP) of its child node, triggering a value change once the AP reaches a fuzzy threshold. Multiple NUTs may be crossed together producing a novel NUTs. The transition time in a NUTs, in response to a â??surprise,â?? is characterized, and the formalism is evaluated in the context of a non-trivial application: Autonomous Driving with imperfect sensors. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
AV  - none
EP  - 871
VL  - 204
JF  - Lecture Notes in Networks and Systems
A1  - Zakaria, N.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111964038&doi=10.1007%2f978-981-16-1089-9_66&partnerID=40&md5=3a0cb4771da002d950ef2819caf30f07
PB  - Springer Science and Business Media Deutschland GmbH
SN  - 23673370
Y1  - 2021///
ER  -