Can massive modularity explain human intelligence? Information control problem and implications for cognitive architecture

Synthese ◽  
2019 ◽  
Author(s):  
Linus Ta-Lun Huang
Author(s):  
Roman Dushkin

This article describes the author's proposal of cognitive architecture for the development of artificial intelligence agent of the general level (“strong" artificial intelligence”). The new principles for the development of such architecture are offered: hybrid approach in artificial intelligence and psychophysiological foundations. The scheme of architecture of the proposed solution, as well as the descriptions of possible areas of implementation are given. Strong artificial intelligence represents a technical solution that can solve arbitrary cognitive tasks accessible to humans (human level intelligence), and even beyond the capabilities of human intelligence (artificial superintelligence). The areas of application of strong artificial intelligence are limitless – from solving the current problems faced by humans to completely new tasks that are yet inaccessible to human civilization or expect for their groundbreaker. This study would be interested to the scholars, engineers and researchers dealing with artificial intelligence, as well as to the readers who want to keep in step with modern technologies. The novelty consists in the original approach towards building a cognitive architecture that has absorbed the results of previous research in the area of artificial intelligence. The relevance of this work is based on the indisputable fact that currently, the research in the area of weak artificial intelligence begin to slow down due to the inability to solve general problems, and the majority of national strategies of the advanced countries in the area of artificial intelligence declare the need for the development of new artificial intelligence technologies, including the artificial intelligence of general level.


2021 ◽  
Vol 932 ◽  
Author(s):  
Bo Jin ◽  
Simon J. Illingworth ◽  
Richard D. Sandberg

We consider linear feedback control of the two-dimensional flow past a cylinder at low Reynolds numbers, with a particular focus on the optimal placement of a single sensor and a single actuator. To accommodate the high dimensionality of the flow, we compute its leading resolvent forcing and response modes to enable the design of $\mathcal {H}_2$ -optimal estimators and controllers. We then investigate three control problems: (i) optimal estimation (OE) in which we measure the flow at a single location and estimate the entire flow; (ii) full-state information control (FIC) in which we measure the entire flow but actuate at only one location; and (iii) the overall feedback control problem in which a single sensor is available for measurement and a single actuator is available for control. We characterize the performance of these control arrangements over a range of sensor and actuator placements and discuss implications for effective feedback control when using a single sensor and a single actuator. The optimal sensor and actuator placements found for the OE and FIC problems are also compared with those found for the overall feedback control problem over a range of Reynolds numbers. This comparison reveals the key factors and conflicting trade-offs that limit feedback control performance.


2018 ◽  
Vol 854 ◽  
pp. 34-55 ◽  
Author(s):  
Stephan F. Oehler ◽  
Simon J. Illingworth

We consider feedback flow control of the linearised complex Ginzburg–Landau system. The particular focus is on any trade-offs present when placing a single sensor and a single actuator. The work is presented in three parts. First, we consider the estimation problem in which a single sensor is used to estimate the entire flow field (without any control). Second, we consider the full information control problem in which the entire flow field is known, but only a single actuator is available for control. By considering the optimal sensor placement and optimal actuator placement while varying the stability of the system, a fundamental trade-off for both problems is made clear. Third, we consider the overall feedback control problem in which only a single sensor is available for measurement; and only a single actuator is available for control. By varying the stability of the system, similar fundamental trade-offs are made clear. We discuss implications for effective feedback control with a single sensor and a single actuator and compare it to previous placement methods.


2020 ◽  
Vol 43 ◽  
Author(s):  
Chris Fields ◽  
James F. Glazebrook

Abstract Gilead et al. propose an ontology of abstract representations based on folk-psychological conceptions of cognitive architecture. There is, however, no evidence that the experience of cognition reveals the architecture of cognition. Scale-free architectural models propose that cognition has the same computational architecture from sub-cellular to whole-organism scales. This scale-free architecture supports representations with diverse functions and levels of abstraction.


1973 ◽  
Vol 18 (9) ◽  
pp. 416-417
Author(s):  
MARJORIE P. HONZIK
Keyword(s):  

1966 ◽  
Vol 11 (6) ◽  
pp. 317-317
Author(s):  
No authorship indicated
Keyword(s):  

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