Intelligent control-operating systems in uncertain environments

2005 ◽  
pp. 215-236 ◽  
Author(s):  
George N. Saridis
Keyword(s):  
Operating Systems ◽  
Intelligent Control ◽  
Uncertain Environments

Context-Driven Proactive Decision Support for Hybrid Teams

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 41-57
Author(s):  
Manisha Mishra ◽  
Pujitha Mannaru ◽  
David Sidoti ◽  
Adam Bienkowski ◽  
Lingyi Zhang ◽  
...  
Keyword(s):  
Decision Support ◽  
Situational Awareness ◽  
Feature Space ◽  
Human Interaction ◽  
Superior Performance ◽  
Uncertain Environments ◽  
Cognitive States ◽  
Contextual Elements ◽  
Human Operators ◽  
Smart Machine

A synergy between AI and the Internet of Things (IoT) will significantly improve sense-making, situational awareness, proactivity, and collaboration. However, the key challenge is to identify the underlying context within which humans interact with smart machines. Knowledge of the context facilitates proactive allocation among members of a human–smart machine (agent) collective that balances auto­nomy with human interaction, without displacing humans from their supervisory role of ensuring that the system goals are achievable. In this article, we address four research questions as a means of advancing toward proactive autonomy: how to represent the interdependencies among the key elements of a hybrid team; how to rapidly identify and characterize critical contextual elements that require adaptation over time; how to allocate system tasks among machines and agents for superior performance; and how to enhance the performance of machine counterparts to provide intelligent and proactive courses of action while considering the cognitive states of human operators. The answers to these four questions help us to illustrate the integration of AI and IoT applied to the maritime domain, where we define context as an evolving multidimensional feature space for heterogeneous search, routing, and resource allocation in uncertain environments via proactive decision support systems.

A Review on Internet of Things’ Operating Systems, Platforms and Applications

2017 ◽  
Author(s):  
Rebin B. Khoshnaw ◽  
Dana F. Doghramach ◽  
Mazin S. Al-Hakeem
Keyword(s):  
Internet Of Things ◽  
Operating Systems

COMMUNICATION OF COMMON AND MARGINAL CHARACTERISTICS OF CONDITIONS IN A TWO-CHANNEL SYSTEM WITH SIMPLE STREAMLINES OF APPLICATIONS

2017 ◽  
pp. 7-19 ◽  
Author(s):  
Georgiy Aleksandrovich Popov
Keyword(s):  
Operating Systems ◽  
Queue Length ◽  
Recurrence Relations ◽  
Queuing Systems ◽  
Channel System ◽  
Current Period ◽  
Multichannel Systems ◽  
Incoming Call ◽  
Marginal Values ◽  
Time Required

The article deals with a two-channel queuing system with a Poisson incoming call flow, in which the application processing time on each of the devices is different. Such models are used, in particular, when describing the operation of the system for selecting service requests in a number of operating systems. A complex system characteristic was introduced at the time of service endings on at least one of the devices, including the queue length, the remaining service time on the occupied device, and the time since the beginning of the current period of employment. This characteristic determines the state of the system at any time. Recurrence relations are obtained that connect this characteristic with its marginal values when there is no queue in the system. The method of introducing additional events was chosen as one of the main methods for analyzing the model. The relationships presented in this article can be used for analysis of the average characteristics of this system, as well as in the process of its simulation. Summarizing the results of work on multichannel systems with an arbitrary number of servicing devices will significantly reduce the time required for simulating complex systems described by sets of multichannel queuing systems.

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