"Thinking-Understanding" Approach in Spiking Reasoning System

被引：0

作者：

Toschev, Alexander ^{[1
]}

Talanov, Max ^{[1
]}

Kurnosov, Vitaliy ^{[2
]}

机构：

[1] Kazan Fed Univ, Kazan, Russia

[2] Kazan Natl Res Technol Univ, Kazan, Russia

来源：

AGENT AND MULTI-AGENT SYSTEMS: TECHNOLOGY AND APPLICATIONS | 2018年 / 74卷

关键词：

Spiking neural networks; Artificial emotions; Affective computing; STATE;

D O I：

10.1007/978-3-319-59394-4_17

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this position paper we propose the approach to use "Thinking-Understanding" architecture for the management of the real-time operated robotic system. Based on the "Robot dream" architecture, the robotic system digital input is been translated in form of "pseudo-spikes" and provided to a simulated spiking neural network, then elaborated and fed back to a robotic system as updated behavioural strategy rules. We present the reasoning rule-based system for intelligent spike processing translating spikes into software actions or hardware signals is thus specified. The reasoning is based on pattern matching mechanisms that activates critics that in their turn activates other critics or ways to think inherited from the work of Marvin Minsky "The emotion machine" [7].

引用

页码：171 / 177

页数：7

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