The Semiotics of Cybernetic Percept-Action Systems

2011 ◽  
Vol 1 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Peter Cariani
Keyword(s):  
Performance Measures ◽  
Physical Systems ◽  
Action Systems ◽  
Sign Systems ◽  
Operational Systems ◽  
Functional Sign ◽  
Physical Construction ◽  
Semantic Closure ◽  
Operational Structure

In this paper, a semiotic framework for natural and artificial adaptive percept-action systems is presented. The functional organizations and operational structures of percept-action systems with different degrees of adaptivity and self-construction are considered in terms of syntactic, semantic, and pragmatic relations. Operational systems-theoretic criteria for distinguishing semiotic, sign-systems from nonsemiotic physical systems are proposed. A system is semiotic if a set of functional sign-states can be identified, such that the system’s behavior can be effectively described in terms of operations on sign-types. Semiotic relations involved in the operational structure of the observer are outlined and illustrated using the Hertzian commutation diagram. Percept-action systems are observers endowed with effectors that permit them to act on their surrounds. Percept-action systems consist of sensors, effectors, and a coordinative part that determines which actions will be taken. Cybernetic systems adaptively steer behavior by altering percept-action mappings contingent on evaluated performance measures via embedded goals. Self-constructing cybernetic systems use signs to direct the physical construction of all parts of the system to create new syntactic, semantic, and pragmatic relations. When a system gains the ability to construct its material hardware and choose its semiotic relations, it achieves a degree of epistemic autonomy, semantic closure, and pragmatic self-direction.

Computer-Aided Generation of Performance Measures for Man-Machine Systems

1974 ◽  
Vol 18 (3) ◽  
pp. 359-367 ◽  
Author(s):  
Edward M. Connelly ◽  
Patricia A. Knoop ◽  
Francis J. Bourne ◽  
Diane G. Loental
Keyword(s):  
Performance Measures ◽  
Reliability And Validity ◽  
Test System ◽  
Training Systems ◽  
Objective Performance Measures ◽  
Operational Systems ◽  
Improved Performance ◽  
Machine Systems ◽  
Validation Tests ◽  
Candidate Performance

The design, application, and evaluation of man-machine systems are limited by our ability to measure system performance in a reliable and sensitive manner. Without adequate performance measures, there is no way to test system designs, to plan and execute training systems, or to effectively evaluate operational systems. Typically, measures are manually produced by selecting a set of candidate performance measures which are subsequently tested for reliability and validity. Since the measurement value of a given candidate measure is not known until these tests are complete, this process, which may be an iterative process, can be both time consuming and costly. Also, since only a few candidate measures can be investigated manually, there is a high probability that superior measures are not even considered. Automating at least some of the manual operations required can result in improved performance measures in less time and at lower cost. The performance measurement generating processor described in this paper accepts demonstration data representing various levels of performance, and under user control, analyzes the data to provide candidate performance measures. The processor also conducts validation tests and orders candidate measures according to their measurement value. Output from the FORTRAN IV processor includes results from validation tests and specifications for objective performance measures.

Cyber-physical systems integration of building information models and the physical construction

2015 ◽  
Vol 22 (5) ◽  
pp. 516-535 ◽  
Author(s):  
Abiola Akanmu ◽  
Chimay J. Anumba
Keyword(s):  
Real Time ◽  
Construction Industry ◽  
Information Exchange ◽  
Cyber Physical Systems ◽  
Full Potential ◽  
System Architectures ◽  
Content Type ◽  
Physical Systems ◽  
Virtual Models ◽  
Physical Construction

Purpose – In spite of the benefits of virtual models in the building and construction industry, the full potential of these models, especially in the construction and operation phases, remains largely unrealized. With the increasing developments in information and communication technology, a number of attempts have been made to extend the use of these models, through the development of integration approaches and technologies. However, the issue of integrating the virtual model and the physical construction such as to enable bi-directional coordination, has not been adequately addressed. Thus, the purpose of this paper is to investigate the application of a cyber-physical systems (CPS) approach in enhancing bi-directional coordination between virtual models and the physical construction. Design/methodology/approach – This research employs scenario development rapid prototyping to illustrate CPS integration in the construction industry, with a particular focus on facilitating bi-directional coordination. The proof-of-concept prototype systems developed were validated using a focus group consisting of industry practitioners. Findings – Bi-directional coordination between virtual models and the physical construction has the potential to improve real-time progress monitoring and control of the construction process, tracking of changes and model updates, information exchange between the design office and the job site, real-time documentation of the as-built status of high-value components and improved sustainability practices. Originality/value – This paper adds value to the construction industry by demonstrating the application of the CPS approach in enhancing bi-directional coordination between virtual models and the physical construction through the development of system architectures, scenarios and prototype systems.

scholarly journals AUTONOMOUS SYSTEMS: COGNITIVE CALCULATIONS ON THE PRINCIPLES OF THE BOUNDARY GENERALIZATIONS PARADIGM

2021 ◽  
pp. 263-267
Author(s):  
Yurii Prokopchuk
Keyword(s):  
Intelligent Systems ◽  
Data Science ◽  
Autonomous Systems ◽  
Cognitive Networks ◽  
Sense Making ◽  
Space Robotics ◽  
Software Support ◽  
Physical Systems ◽  
Operational Systems ◽  
Living Being

Research in the field of Autonomous Systems focuses on the development of machines and robots that are able to perceive their environment autonomously and to interact with it like a living being. This field of research includes such areas as Autonomous Intelligent Systems, Cognitive Technical Systems, Autonomous Perception and Decision Making, Cognitive/Urgent Computation, Cyber-Physical Systems, Artificial Intelligence (AI), AI Assistants, Sense-Making Platform, Cognitive Operational Systems, Cognitive Networks/Internet, Autonomous Space Robotics, Machine Learning, Big Data Calculus, Data Science Machine Eliminates Human Intuition, and simulation. The report examines the mathematical and software support of autonomous systems. The necessity of deep intellectualization of autonomous systems for space purposes is substantiated.

Development of Sensitive Performance Measures for Selection of Crews for Flight Training

1982 ◽  
Vol 26 (10) ◽  
pp. 825-829 ◽  
Author(s):  
Edward M. Connelly ◽  
Brian D. Shipley
Keyword(s):  
Performance Measures ◽  
Test System ◽  
Empirical Method ◽  
Performance Criteria ◽  
Flight Training ◽  
Training Systems ◽  
Student Pilots ◽  
Controlled Systems ◽  
Operational Systems ◽  
Rotary Wing

Performance of operator controlled systems is limited by our ability to measure system and component subsystem performance in a reliable and sensitive manner. Without adequate performance measures, there is no way to produce and test system designs, plan and execute training systems, or evaluate operational systems. Methods of developing these performance measures can be characterized by the way in which performance criteria are obtained. One approach which can be used when all factors that limit performance are known and quantified is an analytical method. For example, if a problem requires that an aircraft climb to a specified altitude while conserving fuel during the climb, the criterion, i.e., minimization of fuel, could be precisely defined analytically. Frequently, however, problems cannot be solved analytically, but demonstrations of superior as well as less than superior performances are available. In these cases an empirical approach can be used. This paper describes an empirical method for analyzing simulator flight data to develop weightings that permit performance discrimination between two groups of student pilots (one group of students successfully passed the initial Army rotary wing training program at Ft. Rucker, Alabama. The other group of students did not pass that training course.). The paper provides a description of the job sample (flight training) tests used to collect the data, the method for synthesizing the performance measures, and the results from using the measures to score student pilots.

Dynamic similarities in action systems

1996 ◽  
Vol 19 (1) ◽  
pp. 71-72
Author(s):  
Allen W. Burton
Keyword(s):  
Performance Measures ◽  
Task Analysis ◽  
Movement Patterns ◽  
Global Dynamics ◽  
Action Systems ◽  
Action System ◽  
Insight Into

AbstractLatash & Anson's contention that movement patterns that are different from those typically observed in persons without impairments should not be considered abnormal and usually should not be corrected is consistent with Davis & Burton's Ecological Task Analysis (ETA). Extending from the ETA concept of performer-scaled performance measures, the use of Froude numbers may offer insight into the global dynamics of a person's action system.

Cyber-Physical Systems Framework for Smart Built-Environments

2019 ◽  
pp. 129-148 ◽  
Author(s):  
Yaseen Srewil ◽  
Raimar J. Scherer
Keyword(s):  
Systems Approach ◽  
Cyber Physical Systems ◽  
Control Flow ◽  
Built Environments ◽  
Physical Systems ◽  
Building Models ◽  
Data Capturing ◽  
And Control ◽  
Systems Framework ◽  
Physical Construction

Cyber-physical systems (CPS) can be seen as digitally-driven technological fusions of physical, spatial and virtual models. Thereby, the construction entities, locations and processes are tightly linked to the digital building models (BIM) using automated data capturing (ADC) solutions. This chapter focuses on the challenge of modelling a cyber–physical systems approach for constructing domains in order to effectively exploit the computation, control and communication capabilities. Pairing BIM and ADC technologies offers an adequate solution bridging the information gaps and promoting the collaboration among digital, spatial and physical construction entities. The results are cyber-physical objects (CPOs) at a level of “smartness” that provides enhancement of digital capabilities and the ability of context-awareness. These hybrid objects of digital equivalents and physical entities can be embedded in the construction and logistics processes in order to track progress and monitor the construction site activities and control flow close to real-time.

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