Complex Adaptive Systems
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The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.
The ACC is the annual conference of the American Automatic Control Council (AACC, the U.S. national member organization of the International Federation for Automatic Control (IFAC)). The ACC is internationally recognized as a premier scientific and engineering conference dedicated to the advancement of control theory and practice. The ACC brings together an international community of researchers and practitioners to discuss the latest findings in automatic control. The 2020 ACC technical program will
AMC2020 is the 16th in a series of biennial international workshops on Advanced Motion Control which aims to bring together researchers from both academia and industry and to promote omnipresent motion control technologies and applications.
The aim of the conference will be to bring together the majority of leading expert scientists, thought leaders and forward looking professionals from all domains of Intelligent Transportation Systems, to share ongoing research achievements, to exchange views and knowledge and to contribute to the advances in the field. The main theme of the conference will be “ITS within connected, automated and electric multimodal mobility systems and services”.
The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.
The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.
Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
2013 6th International Conference on Information Management, Innovation Management and Industrial Engineering, 2013
Open Innovation Alliances (OIAs) have characters of dynamics, heterogeneity, openness, and complexity. Traditional reductionism and mathematical statistics cannot explain emergence, which is the impact of agents of interaction on external environments. Some scholars have proposed to study OIAs in the view of a dynamic adaptive system. This paper clarifies OIAs as complex adaptive systems(CAS) according to properties and mechanism of ...
2009 International Symposium on Collaborative Technologies and Systems, 2009
Business processes are becoming increasingly collaborative and dynamic in nature. Correspondingly computer systems must provide the systems to support both the collaboration and changing work practices. This paper describes the modelling and technical requirements to support such processes. It suggests that any support system must be consistent with the more open nature of dynamic systems and provide the design methods ...
PICMET '07 - 2007 Portland International Conference on Management of Engineering & Technology, 2007
The enterprises agglomerations are becoming an interesting study topic, so several authors are sure that the interactions and geographic proximity have a strong impact in the competition and innovation of the enterprises of the clusters (T. Altenburg and J. Meyer-Stamer), (P. Krugman, 1999), (M. Porter, 2004). So it is also possible to talk about "learning clusters", knowledge accumulated, and knowledge ...
IEEE Systems Journal, 2012
The objective of this paper is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in a certain engineered complex adaptive system. A conceptual framework is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The proposed modeling approach allows examining complexity in the structure ...
Artificial Life, 2006
Visualization has an increasingly important role to play in scientific research. Moreover, visualization has a special role to play within artificial life as a result of the informal status of its key explananda: life and complexity. Both are poorly defined but apparently identifiable via raw inspection. Here we concentrate on how visualization techniques might allow us to move beyond this ...
Adaptive Learning and Optimization for MI: From the Foundations to Complex Systems - Haibo He - WCCI 2016
Robotics History: Narratives and Networks Oral Histories: Minoru Asada
Philippe Wolf: Designing Secure and Private Complex Data Systems - WF-IoT 2015
A 30-MHz-to-3-GHz CMOS Array Receiver with Frequency and Spatial Interference Filtering for Adaptive Antenna Systems: RFIC Industry Showcase
Overcoming the Static Learning Bottleneck - the Need for Adaptive Neural Learning - Craig Vineyard: 2016 International Conference on Rebooting Computing
Multiple Sensor Fault Detection and Isolation in Complex Distributed Dynamical Systems
MicroApps: Simulation of Airborne, Space-Borne and Ship-Based Radar Systems with Complex Environment (Agilent EEsof)
Safety Synergies and Engineering Opportunities Complex Systems in Life Sciences
Soumya Kanti Datta: Connected Cars as Complex Systems - IoT Challenges Industry Forum Panel: WF IoT 2016
Innovative Transmission Line Measurement and Characterization Reduce Time to Repair for Complex Communication Systems: MicroApps 2015 - Keysight Technologies
Neuromorphic Adaptive Edge-preserving Denoising Filter: IEEE Rebooting Computing 2017
Fragility of Interconnected Cyber-Physical Systems - Marios M. Polycarpou - WCCI 2016
Q&A - IoT Challenges Industry Forum Panel: WF IoT 2016
Said Tabet: IoT Moving Forward - IoT Challenges Industry Forum Panel: WF IoT 2016
Lillie Coney on the IoT and the Ability to Defend Against the Silent Intruder: 2016 End to End Trust and Security Workshop for the Internet of Things
ICASSP 2010 - Advances in Neural Engineering
Norha Villegas: The Role of Models at Runtime in Smart Cyber Physical Systems: WF IoT 2016
Life Sciences: Mary Capelli-Schellpfeffer on engineering safety
Q&A with Dr. Al Emondi: IEEE Brain Podcast, Episode 13
Open Innovation Alliances (OIAs) have characters of dynamics, heterogeneity, openness, and complexity. Traditional reductionism and mathematical statistics cannot explain emergence, which is the impact of agents of interaction on external environments. Some scholars have proposed to study OIAs in the view of a dynamic adaptive system. This paper clarifies OIAs as complex adaptive systems(CAS) according to properties and mechanism of CAS based on prior research. This study illustrates that open innovation alliance is a complex adaptive system and responds quickly to environmental changes. Furthermore, the properties and mechanisms of CAS in OIAs provide a useful framework for designing agent-based models on the next step.
Business processes are becoming increasingly collaborative and dynamic in nature. Correspondingly computer systems must provide the systems to support both the collaboration and changing work practices. This paper describes the modelling and technical requirements to support such processes. It suggests that any support system must be consistent with the more open nature of dynamic systems and provide the design methods and technical support systems to support them. The paper describes a collaborative metamodel to model dynamic systems and ways to convert the models to implementations. The paper stresses the need for lightweight technologies to support dynamic systems and uses the models to define requirements of such technologies.
The enterprises agglomerations are becoming an interesting study topic, so several authors are sure that the interactions and geographic proximity have a strong impact in the competition and innovation of the enterprises of the clusters (T. Altenburg and J. Meyer-Stamer), (P. Krugman, 1999), (M. Porter, 2004). So it is also possible to talk about "learning clusters", knowledge accumulated, and knowledge constructed in a collective form. For the study of these shapes of post-fordists production organizations and for the many variables that they present new frameworks are necessary, one of them is the complex adaptive systems theory. The model of the complex adaptive systems permits to evaluate multiple interactions between different agents and the impact of the agent's action in the system. This focus permits to find news and unexpected models from the interactions between the parts ofthe open systems. The present paper has the aim of studying: the dynamic interaction, the knowledge transfer, the learning, and the evolution of the Ica wine cluster in Peru with that model. In this context, the research questions are: what is the dynamic of the interactions between enterprises of the cluster?, how is the knowledge transferred?, how does the cluster learn?, and how is the technological evolution of this cluster? The methodology is the elaboration of a theoretical model that integrates the concepts of characteristics of the clusters and complex adaptive systems, then accordingly this theoretical model is elaborated a questionnaire, after that the questionnaire is applied to a wine and grape cluster, finally the main conclusions and recommendations are obtained. The results of the research will be an important document for the actions, strategic decisions and improvement of the interactions between cluster agents.
The objective of this paper is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in a certain engineered complex adaptive system. A conceptual framework is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The proposed modeling approach allows examining complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. Electrical power demand is used to illustrate the applicability of the modeling approach. We describe and use the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build our framework. The framework allows focus on the critical factors of an engineered system, but also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems without complex modeling. This paper adopts concepts of complex systems science to management science and system-of- systems engineering.
Visualization has an increasingly important role to play in scientific research. Moreover, visualization has a special role to play within artificial life as a result of the informal status of its key explananda: life and complexity. Both are poorly defined but apparently identifiable via raw inspection. Here we concentrate on how visualization techniques might allow us to move beyond this situation by facilitating increased understanding of the relationships between an ALife system's (low-level) composition and organization and its (high-level) behavior. We briefly review the use of visualization within artificial life, and point to some future developments represented by the articles collected within this special issue.
This article bases on the view of complex adaptive systems theory to give the methodological analysis to the wireless sensor network (WSN)'s Self- configuration, Self-healing and Agent characteristics. Wireless Sensor Network is a complex system. Based on scientific management research methodology, it must use the complex system theory to deal with complex systems. CAS gives high potential line of thought to study wireless sensor network in methodology.
Simulation-based decision support is an important tool in business, science, engineering, and many other areas. Although traditional simulation analysis can be used to generate and test possible plans, it suffers from a long cycle time for model update, analysis and verification. It is thus very difficult to carry out prompt "what-if' analysis to respond to abrupt changes in the physical systems being modeled. Symbiotic simulation has been proposed as a way of solving this problem by having the simulation system and the physical system interact in a mutually beneficial manner. The simulation system benefits from real-time input data which is used to adapt the model and the physical system benefits from the optimized performance that is obtained from the analysis of simulation results. This talk will present a classification of symbiotic simulation systems with examples of applications from the literature. An analysis of these applications reveals some common aspects and issues that are important for symbiotic simulation systems. From this analysis, we have specified an agent-based generic framework for symbiotic simulation. We show that it is possible to identify a few basic functionalities that can be provided by corresponding agents in our framework. These can then be composed together by a specific workflow to form a particular symbiotic simulation system. Finally, the talk will discuss the use of symbiotic simulation as a decision support tool in understanding and steering complex adaptive systems. Some examples of current applications being developed at Nanyang Technological University will be described.
The rise of automation in many systems and technology ubiquity in general, present complex operational environments that require a solution that can continually morph to meet the changing demands of the operational situation. This paper presents a research project that is developing theory and exploring concepts for engineering complex adaptive systems of systems. The research builds on a developing body of knowledge in complex systems, complex adaptive systems, and systems of systems engineering to apply engineered complex adaptive systems of systems as a solution to challenging multi-dimensional problems such as the emerging naval concept for distributed lethality. A comprehensive study for engineering complex adaptive systems of systems solutions, as well as a method for identifying and developing effective responses to naturally-occurring, human modified, and human made complex adaptive systems of systems will build a new body of knowledge in systems engineering. This paper frames the author's research project and approach.
Self-organization and adaptability are critical properties of complex adaptive systems (CAS), and their analysis provides insight into the design of these systems, consequently leading to real-world advancements. However, these properties are difficult to analyze in real-world scenarios due to performance constraints, metric design, and limitations in existing modeling tools. Several metrics have been proposed for their identification, but metric effectiveness under the same experimental settings has not been studied before. In this paper we present an observation tool, part of a complex adaptive systems modeling framework, that allows for the analysis of these metrics for large-scale complex models. We compare and contrast a wide range of metrics implemented in our observation tool. Our experimental analysis uses the classic model of Game of Life to provide a baseline for analysis, and a more complex Emergency Department model to further explore the suitability of these metrics and the modeling and analysis challenges faced when using them.
Complex Adaptive Systems are systems composed of distributed, decentralized and autonomous agents (software components, systems and people) and exhibit non-deterministic interactions between these agents. These interactions can often lead to the appearance of "emergent" behaviour or properties at the system level. These emergents can be harmful to the system or individual constituents, but are by their nature impossible to predict in advance and must therefore be detected at run-time. The characteristics of these systems mean that detecting emergence at run-time presents a significant challenge, one that cannot be met by existing methods that depend on a centralized controller with a global view of the system state. In this paper we present an important step towards decentralised detection of emergence in Complex Adaptive Systems. Our approach is based on observing the consequence of naturally arising feedback that occurs from the system level (macro) to the component level (micro) when emergent behaviour or properties appear in a system. This feedback results in the appearance of correlations, where none existed before, between the internal variables of individual agents and the properties that an agent detects in its local environment. In a case study of five different multi-agent systems we demonstrate that the number of agents that report these correlations increases as emergence occurs in each system. This provides the constituent agents with sufficient information to collaboratively detect when emergence has occurred at a system level without the need for a centralized, global view of the system.
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