The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Danny Weyns - One of the best experts on this subject based on the ideXlab platform.
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software engineering of self Adaptive Systems
Handbook of Software Engineering, 2019Co-Authors: Danny WeynsAbstract:Modern software Systems are expected to operate under uncertain conditions, without interruption. Possible causes of uncertainties include changes in the operational environment, dynamics in the availability of resources, and variations of user goals. The aim of self-adaptation is to let the system collect additional data about the uncertainties during operation. The system uses the additional data to resolve uncertainties, to reason about itself, and based on its goals to reconfigure or adjust itself to satisfy the changing conditions, or if necessary to degrade gracefully. In this chapter, we provide a particular perspective on the evolution of the field of self-adaptation in six waves. These waves put complementary aspects of engineering self-Adaptive Systems in focus that synergistically have contributed to the current knowledge in the field. From the presented perspective on the field, we outline a number of challenges for future research in self-adaptation, both in a short and long term.
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a systematic literature review on methods that handle multiple quality attributes in architecture based self Adaptive Systems
Information & Software Technology, 2017Co-Authors: Danny Weyns, Sara Mahdavihezavehi, Vinicius H S Durelli, Paris AvgeriouAbstract:Abstract Context Handling multiple quality attributes (QAs) in the domain of self-Adaptive Systems is an understudied research area. One well-known approach to engineer Adaptive software Systems and fulfill QAs of the system is architecture-based self-adaptation. In order to develop models that capture the required knowledge of the QAs of interest, and to investigate how these models can be employed at runtime to handle multiple quality attributes, we need to first examine current architecture-based self-Adaptive methods. Objective In this paper we review the state-of-the-art of architecture-based methods for handling multiple QAs in self-Adaptive Systems. We also provide a descriptive analysis of the collected data from the literature. Method We conducted a systematic literature review by performing an automatic search on 28 selected venues and books in the domain of self-Adaptive Systems. As a result, we selected 54 primary studies which we used for data extraction and analysis. Results Performance and cost are the most frequently addressed set of QAs. Current self-Adaptive Systems dealing with multiple QAs mostly belong to the domain of robotics and web-based Systems paradigm. The most widely used mechanisms/models to measure and quantify QAs sets are QA data variables. After QA data variables, utility functions and Markov chain models are the most common models which are also used for decision making process and selection of the best solution in presence of many alternatives. The most widely used tools to deal with multiple QAs are PRISM and IBM's autonomic computing toolkit. KLAPER is the only language that has been specifically developed to deal with quality properties analysis. Conclusions Our results help researchers to understand the current state of research regarding architecture-based methods for handling multiple QAs in self-Adaptive Systems, and to identity areas for improvement in the future. To summarize, further research is required to improve existing methods performing tradeoff analysis and preemption, and in particular, new methods may be proposed to make use of models to handle multiple QAs and to enhance and facilitate the tradeoffs analysis and decision making mechanism at runtime.
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software engineering for self Adaptive Systems research challenges in the provision of assurances
International Seminar on Software Engineering for Self-Adaptive Systems: Assurances 2013, 2017Co-Authors: Rogerio De Lemos, Bradley Schmerl, David Garlan, Danny Weyns, Holger Giese, Marin Litoiu, Jesper Andersson, Carlo Ghezzi, Luciano Baresi, Nelly BencomoAbstract:The important concern for modern software Systems is to become more cost-effective, while being versatile, flexible, resilient, dependable, energy-efficient, customisable, configurable and self-optimising when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip software Systems with self-managing capabilities using self-adaptation mechanisms. Despite recent advances in this area, one key aspect of self-Adaptive Systems that remains to be tackled in depth is the provision of assurances, i.e., the collection, analysis and synthesis of evidence that the system satisfies its stated functional and non-functional requirements during its operation in the presence of self-adaptation. The provision of assurances for self-Adaptive Systems is challenging since run-time changes introduce a high degree of uncertainty. This paper on research challenges complements previous roadmap papers on software engineering for self-Adaptive Systems covering a different set of topics, which are related to assurances, namely, perpetual assurances, composition and decomposition of assurances, and assurances obtained from control theory. This research challenges paper is one of the many results of the Dagstuhl Seminar 13511 on Software Engineering for Self-Adaptive Systems: Assurances which took place in December 2013.
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software engineering for self Adaptive Systems research challenges in the provision of assurances
Software Engineering for Self-Adaptive Systems, 2017Co-Authors: Rogerio De Lemos, Bradley Schmerl, David Garlan, Danny Weyns, Holger Giese, Marin Litoiu, Jesper Andersson, Carlo Ghezzi, Luciano Baresi, Nelly BencomoAbstract:The important concern for modern software Systems is to become more cost-effective, while being versatile, flexible, resilient, dependable, energy-efficient, customisable, configurable and self-optimising when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip software Systems with self-managing capabilities using self-adaptation mechanisms. Despite recent advances in this area, one key aspect of self-Adaptive Systems that remains to be tackled in depth is the provision of assurances, i.e., the collection, analysis and synthesis of evidence that the system satisfies its stated functional and non-functional requirements during its operation in the presence of self-adaptation. The provision of assurances for self-Adaptive Systems is challenging since run-time changes introduce a high degree of uncertainty. This paper on research challenges complements previous roadmap papers on software engineering for self-Adaptive Systems covering a different set of topics, which are related to assurances, namely, perpetual assurances, composition and decomposition of assurances, and assurances obtained from control theory. This research challenges paper is one of the many results of the Dagstuhl Seminar 13511 on Software Engineering for Self-Adaptive Systems: Assurances which took place in December 2013.
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MAPE-K Formal Templates to Rigorously Design Behaviors for Self-Adaptive Systems
ACM Transactions on Autonomous and Adaptive Systems, 2015Co-Authors: Didac Gil De La Iglesia, Danny WeynsAbstract:Designing software Systems that have to deal with dynamic operating conditions, such as changing availability of resources and faults that are difficult to predict, is complex. A promising approach to handle such dynamics is self-adaptation that can be realized by a MAPE-K feedback loop (Monitor-Analyze-Plan-Execute plus Knowledge). To provide evidence that the system goals are satisfied, given the changing conditions, the state of the art advocates the use of formal methods. However, little research has been done on consolidating design knowledge of self-Adaptive Systems. To support designers, this paper contributes with a set of formally specified MAPE-K templates that encode design expertise for a family of self-Adaptive Systems. The templates comprise: (1) behavior specification templates for modeling the different components of a MAPE-K feedback loop (based on networks of timed automata), and (2) property specification templates that support verification of the correctness of the adaptation behaviors (based on timed computation tree logic). To demonstrate the reusability of the formal templates, we performed four case studies in which final-year Masters students used the templates to design different self-Adaptive Systems.
Jesper Andersson - One of the best experts on this subject based on the ideXlab platform.
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software engineering for self Adaptive Systems research challenges in the provision of assurances
International Seminar on Software Engineering for Self-Adaptive Systems: Assurances 2013, 2017Co-Authors: Rogerio De Lemos, Bradley Schmerl, David Garlan, Danny Weyns, Holger Giese, Marin Litoiu, Jesper Andersson, Carlo Ghezzi, Luciano Baresi, Nelly BencomoAbstract:The important concern for modern software Systems is to become more cost-effective, while being versatile, flexible, resilient, dependable, energy-efficient, customisable, configurable and self-optimising when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip software Systems with self-managing capabilities using self-adaptation mechanisms. Despite recent advances in this area, one key aspect of self-Adaptive Systems that remains to be tackled in depth is the provision of assurances, i.e., the collection, analysis and synthesis of evidence that the system satisfies its stated functional and non-functional requirements during its operation in the presence of self-adaptation. The provision of assurances for self-Adaptive Systems is challenging since run-time changes introduce a high degree of uncertainty. This paper on research challenges complements previous roadmap papers on software engineering for self-Adaptive Systems covering a different set of topics, which are related to assurances, namely, perpetual assurances, composition and decomposition of assurances, and assurances obtained from control theory. This research challenges paper is one of the many results of the Dagstuhl Seminar 13511 on Software Engineering for Self-Adaptive Systems: Assurances which took place in December 2013.
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software engineering for self Adaptive Systems research challenges in the provision of assurances
Software Engineering for Self-Adaptive Systems, 2017Co-Authors: Rogerio De Lemos, Bradley Schmerl, David Garlan, Danny Weyns, Holger Giese, Marin Litoiu, Jesper Andersson, Carlo Ghezzi, Luciano Baresi, Nelly BencomoAbstract:The important concern for modern software Systems is to become more cost-effective, while being versatile, flexible, resilient, dependable, energy-efficient, customisable, configurable and self-optimising when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip software Systems with self-managing capabilities using self-adaptation mechanisms. Despite recent advances in this area, one key aspect of self-Adaptive Systems that remains to be tackled in depth is the provision of assurances, i.e., the collection, analysis and synthesis of evidence that the system satisfies its stated functional and non-functional requirements during its operation in the presence of self-adaptation. The provision of assurances for self-Adaptive Systems is challenging since run-time changes introduce a high degree of uncertainty. This paper on research challenges complements previous roadmap papers on software engineering for self-Adaptive Systems covering a different set of topics, which are related to assurances, namely, perpetual assurances, composition and decomposition of assurances, and assurances obtained from control theory. This research challenges paper is one of the many results of the Dagstuhl Seminar 13511 on Software Engineering for Self-Adaptive Systems: Assurances which took place in December 2013.
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software engineering for self Adaptive Systems a second research roadmap
Dagstuhl Seminar Proceedings, 2013Co-Authors: Rogerio De Lemos, Bradley Schmerl, Holger Giese, Marin Litoiu, Hausi A Muller, Mary Shaw, Jesper Andersson, Gabriel Tamura, Norha M Villegas, Thomas VogelAbstract:The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-Adaptive software Systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-Adaptive solutions, software engineering processes for self-Adaptive Systems, from centralized to decentralized control, and practical run-time verification & validation for self-Adaptive Systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-Adaptive Systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.
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software engineering for self Adaptive Systems a second research roadmap
Dagstuhl Seminar Proceedings, 2013Co-Authors: Rogerio De Lemos, Bradley Schmerl, Holger Giese, Marin Litoiu, Hausi A Muller, Mary Shaw, Jesper Andersson, Gabriel Tamura, Norha M Villegas, Thomas VogelAbstract:The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-Adaptive software Systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-Adaptive solutions, software engineering processes for self-Adaptive Systems, from centralized to decentralized control, and practical run-time verification & validation for self-Adaptive Systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-Adaptive Systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.
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on patterns for decentralized control in self Adaptive Systems
Lecture Notes in Computer Science, 2013Co-Authors: Danny Weyns, Bradley Schmerl, Holger Giese, Jesper Andersson, Vincenzo Grassi, Sam Malek, Raffaela Mirandola, Christian Prehofer, Jochen Wuttke, Karl M GoschkaAbstract:Self-adaptation is typically realized using a control loop. One prominent approach for organizing a control loop in self-Adaptive Systems is by means of four components that are responsible for the primary functions of self-adaptation: Monitor, Analyze, Plan, and Execute, together forming a MAPE loop. When Systems are large, complex, and heterogeneous, a single MAPE loop may not be sufficient for managing all adaptation in a system, so multiple MAPE loops may be introduced. In self-Adaptive Systems with multiple MAPE loops, decisions about how to decentralize each of the MAPE functions must be made. These decisions involve how and whether the corresponding functions from multiple loops are to be coordinated (e.g., planning components coordinating to prepare a plan for an adaptation). To foster comprehension of self-Adaptive Systems with multiple MAPE loops and support reuse of known solutions, it is crucial that we document common design approaches for engineers. As such systematic knowledge is currently lacking, it is timely to reflect on these Systems to: (a) consolidate the knowledge in this area, and (b) to develop a systematic approach for describing different types of control in self-Adaptive Systems. We contribute with a simple notation for describing interacting MAPE loops, which we believe helps in achieving (b), and we use this notation to describe a number of existing patterns of interacting MAPE loops, to begin to fulfill (a). From our study, we outline numerous remaining research challenges in this area.
Holger Giese - One of the best experts on this subject based on the ideXlab platform.
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software engineering for self Adaptive Systems research challenges in the provision of assurances
International Seminar on Software Engineering for Self-Adaptive Systems: Assurances 2013, 2017Co-Authors: Rogerio De Lemos, Bradley Schmerl, David Garlan, Danny Weyns, Holger Giese, Marin Litoiu, Jesper Andersson, Carlo Ghezzi, Luciano Baresi, Nelly BencomoAbstract:The important concern for modern software Systems is to become more cost-effective, while being versatile, flexible, resilient, dependable, energy-efficient, customisable, configurable and self-optimising when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip software Systems with self-managing capabilities using self-adaptation mechanisms. Despite recent advances in this area, one key aspect of self-Adaptive Systems that remains to be tackled in depth is the provision of assurances, i.e., the collection, analysis and synthesis of evidence that the system satisfies its stated functional and non-functional requirements during its operation in the presence of self-adaptation. The provision of assurances for self-Adaptive Systems is challenging since run-time changes introduce a high degree of uncertainty. This paper on research challenges complements previous roadmap papers on software engineering for self-Adaptive Systems covering a different set of topics, which are related to assurances, namely, perpetual assurances, composition and decomposition of assurances, and assurances obtained from control theory. This research challenges paper is one of the many results of the Dagstuhl Seminar 13511 on Software Engineering for Self-Adaptive Systems: Assurances which took place in December 2013.
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software engineering for self Adaptive Systems research challenges in the provision of assurances
Software Engineering for Self-Adaptive Systems, 2017Co-Authors: Rogerio De Lemos, Bradley Schmerl, David Garlan, Danny Weyns, Holger Giese, Marin Litoiu, Jesper Andersson, Carlo Ghezzi, Luciano Baresi, Nelly BencomoAbstract:The important concern for modern software Systems is to become more cost-effective, while being versatile, flexible, resilient, dependable, energy-efficient, customisable, configurable and self-optimising when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip software Systems with self-managing capabilities using self-adaptation mechanisms. Despite recent advances in this area, one key aspect of self-Adaptive Systems that remains to be tackled in depth is the provision of assurances, i.e., the collection, analysis and synthesis of evidence that the system satisfies its stated functional and non-functional requirements during its operation in the presence of self-adaptation. The provision of assurances for self-Adaptive Systems is challenging since run-time changes introduce a high degree of uncertainty. This paper on research challenges complements previous roadmap papers on software engineering for self-Adaptive Systems covering a different set of topics, which are related to assurances, namely, perpetual assurances, composition and decomposition of assurances, and assurances obtained from control theory. This research challenges paper is one of the many results of the Dagstuhl Seminar 13511 on Software Engineering for Self-Adaptive Systems: Assurances which took place in December 2013.
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software engineering for self Adaptive Systems a second research roadmap
Dagstuhl Seminar Proceedings, 2013Co-Authors: Rogerio De Lemos, Bradley Schmerl, Holger Giese, Marin Litoiu, Hausi A Muller, Mary Shaw, Jesper Andersson, Gabriel Tamura, Norha M Villegas, Thomas VogelAbstract:The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-Adaptive software Systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-Adaptive solutions, software engineering processes for self-Adaptive Systems, from centralized to decentralized control, and practical run-time verification & validation for self-Adaptive Systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-Adaptive Systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.
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software engineering for self Adaptive Systems a second research roadmap
Dagstuhl Seminar Proceedings, 2013Co-Authors: Rogerio De Lemos, Bradley Schmerl, Holger Giese, Marin Litoiu, Hausi A Muller, Mary Shaw, Jesper Andersson, Gabriel Tamura, Norha M Villegas, Thomas VogelAbstract:The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-Adaptive software Systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-Adaptive solutions, software engineering processes for self-Adaptive Systems, from centralized to decentralized control, and practical run-time verification & validation for self-Adaptive Systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-Adaptive Systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.
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on patterns for decentralized control in self Adaptive Systems
Lecture Notes in Computer Science, 2013Co-Authors: Danny Weyns, Bradley Schmerl, Holger Giese, Jesper Andersson, Vincenzo Grassi, Sam Malek, Raffaela Mirandola, Christian Prehofer, Jochen Wuttke, Karl M GoschkaAbstract:Self-adaptation is typically realized using a control loop. One prominent approach for organizing a control loop in self-Adaptive Systems is by means of four components that are responsible for the primary functions of self-adaptation: Monitor, Analyze, Plan, and Execute, together forming a MAPE loop. When Systems are large, complex, and heterogeneous, a single MAPE loop may not be sufficient for managing all adaptation in a system, so multiple MAPE loops may be introduced. In self-Adaptive Systems with multiple MAPE loops, decisions about how to decentralize each of the MAPE functions must be made. These decisions involve how and whether the corresponding functions from multiple loops are to be coordinated (e.g., planning components coordinating to prepare a plan for an adaptation). To foster comprehension of self-Adaptive Systems with multiple MAPE loops and support reuse of known solutions, it is crucial that we document common design approaches for engineers. As such systematic knowledge is currently lacking, it is timely to reflect on these Systems to: (a) consolidate the knowledge in this area, and (b) to develop a systematic approach for describing different types of control in self-Adaptive Systems. We contribute with a simple notation for describing interacting MAPE loops, which we believe helps in achieving (b), and we use this notation to describe a number of existing patterns of interacting MAPE loops, to begin to fulfill (a). From our study, we outline numerous remaining research challenges in this area.
Christian Becker - One of the best experts on this subject based on the ideXlab platform.
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Runtime Evolution of the Adaptation Logic in Self-Adaptive Systems
2015 IEEE International Conference on Autonomic Computing, 2015Co-Authors: Felix Maximilian Roth, Christian Krupitzer, Christian BeckerAbstract:Self-Adaptive Systems, which are highly related to Autonomic Computing, are a response to the increasing complexity and size of information Systems. They are able to adapt their behavior to changes in the environment or system resources. A self-Adaptive system consists of managed resources that realize functionality and an adaptation logic that controls the adaptations. So far, many research has been performed on adapting the managed resources. However, only few works cover adapting the adaptation logic, which might be necessary in several cases, e.g., When the architecture of the managed resources changes. This work adresses why adaptation of the adaptation logic might be beneficial, how it can be achieved, and what challenges arise.
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a survey on engineering approaches for self Adaptive Systems
Pervasive and Mobile Computing, 2015Co-Authors: Christian Krupitzer, Felix Maximilian Roth, Sebastian Vansyckel, Gregor Schiele, Christian BeckerAbstract:The complexity of information Systems is increasing in recent years, leading to increased effort for maintenance and configuration. Self-Adaptive Systems (SASs) address this issue. Due to new computing trends, such as pervasive computing, miniaturization of IT leads to mobile devices with the emerging need for context adaptation. Therefore, it is beneficial that devices are able to adapt context. Hence, we propose to extend the definition of SASs and include context adaptation. This paper presents a taxonomy of self-adaptation and a survey on engineering SASs. Based on the taxonomy and the survey, we motivate a new perspective on SAS including context adaptation.
Sheri M Markose - One of the best experts on this subject based on the ideXlab platform.
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computability and evolutionary complexity markets as complex Adaptive Systems cas
The Economic Journal, 2005Co-Authors: Sheri M MarkoseAbstract:Few will argue that the epi-phenomena of biological Systems and socio-economic Systems are anything but complex. The purpose of this Feature is to examine critically and contribute to the burgeoning multi-disciplinary literature on markets as complex Adaptive Systems (CAS). The new sciences of complexity, the principles of self-organisation and emergence along with the methods of evolutionary computation and artificially intelligent agent models have been developed in a multi-disciplinary fashion. The cognoscenti here consider that complex Systems whether natural or artificial, physical, biological or socio-economic can be characterised by a unifying set of principles. Further, it is held that these principles mark a paradigm shift from earlier ways of viewing such phenomenon.
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computability and evolutionary complexity markets as complex Adaptive Systems cas
2004Co-Authors: Sheri M MarkoseAbstract:The purpose of this Feature is to critically examine and to contribute to the burgeoning multi disciplinary literature on markets as complex Adaptive Systems (CAS). Three economists, Robert Axtell, Steven Durlauf and Arthur Robson who have distinguished themselves as pioneers in different aspects of how the thesis of evolutionary complexity pertains to market environments have contributed to this special issue. Axtell is concerned about the procedural aspects of attaining market equilibria in a decentralized setting and argues that principles on the complexity of feasible computation should rule in or out widely held models such as the Walrasian one. Robson puts forward the hypothesis called the Red Queen principle, well known from evolutionary biology, as a possible explanation for the evolution of complexity itself. Durlauf examines some of the claims that have been made in the name of complex Systems theory to see whether these present testable hypothesis for economic models. My overview aims to use the wider literature on complex Systems to provide a conceptual framework within which to discuss the issues raised for Economics in the above contributions and elsewhere. In particular, some assessment will be made on the extent to which modern complex Systems theory and its application to markets as CAS constitutes a paradigm shift from more mainstream economic analysis.
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the new evolutionary computational paradigm of complex Adaptive Systems challenges and prospects for economics and finance
2001Co-Authors: Sheri M MarkoseAbstract:The new evolutionary computational paradigm of market Systems views these as complex Adaptive Systems. The major premise of 18th century classical political economy was that order in market Systems is spontaneous or emergent, in that it is the result of 'human action but not of human design'. This early observation on the disjunction between system wide outcomes and capabilities of micro level rational calculation marks the provenance of modern evolutionary thought. However, it will take a powerful confluence of two 20th century epochal developments for the new evolutionary computational paradigm to rise to the challenge of providing long awaited explanations of what has remained anomalies or outside the ambit of traditional economic analysis. The first of these is the GA¶del-Turing-Post results on incompleteness and algorithmically unsolvable problems that delimit formalist calculation or deductive methods. The second is the Anderson-Holland-Arthur heterogeneous Adaptive agent theory and models for inductive search, emergence and self-organized criticality which can crucially show and explicitly study the processes underpinning the emergence of ordered complexity. Multi-agent model simulation of asset price formation and the innovation based structure changing dynamics of capitalist growth are singled out for analysis of this disjunction between non-anticipating global outcomes and computational micro rationality.
