Topic
Complex adaptive system
About: Complex adaptive system is a research topic. Over the lifetime, 3190 publications have been published within this topic receiving 111947 citations. The topic is also known as: Complex adaptive system, CAS.
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05 Dec 2004
TL;DR: Three applications of agent-based simulations used to analyze military problems are presented, including the MANA model to explore the ability of the U.S. Army's network-based Future Force to perform with degraded communications and how unmanned surface vehicles can be used in force protection missions with the Pythagoras model.
Abstract: There continues to be increasing interest from a broad range of disciplines in agent-based and artificial life simulations. This includes the Department of Defense - which uses simulations heavily in its decision making process. Indeed, military conflicts can have many attributes that are consistent with complex adaptive systems - such as many entities interacting with some degree of autonomy, each of which is continually making decisions to satisfy a variety of sometimes conflicting objectives. In this paper, we present three applications of agent-based simulations used to analyze military problems. The first uses the MANA model to explore the ability of the U.S. Army's network-based Future Force to perform with degraded communications. The second studies how unmanned surface vehicles can be used in force protection missions with the Pythagoras model. The last example examines the standard Army squad size with an integrated effort using MANA, Pythagoras, and the high-resolution simulation JANUS.
108 citations
TL;DR: The characteristics of complex adaptive systems are identified and examples of management errors that may be made when these characteristics are ignored are given.
Abstract: Misspecification of the nature of organizations may be a major reason for difficulty in achieving performance improvement. Organizations are often viewed as machine-like, but complexity science suggests that organizations should be viewed as complex adaptive systems. I identify the characteristics of complex adaptive systems and give examples of management errors that may be made when these characteristics are ignored. Command, control and planning are presented as managerial tasks that come to the fore when a machine view of organizations dominates thinking. When we treat organizations as complex adaptive systems the focus of managerial activity changes, and sensemaking, learning and improvisation become appropriate strategies for performance improvement. Each of these is defined and described. A modest research agenda is presented.
106 citations
TL;DR: In this paper, the authors evaluate the Federal Response Plan (FRP), National Response Plan and National Response Framework (NRF) from the perspectives of interorganizational networks and complex adaptive systems.
Abstract: This article evaluates the Federal Response Plan (FRP), the National Response Plan (NRP), and the National Response Framework (NRF) from the perspectives of interorganizational networks and complex adaptive systems. The article uses the theoretical approach of complexity theory and dynamic network analysis to assess the relationships among organizations using the NRP/NRF as the structure that shapes their functional and organizational relationships. It also examines the applicability of concepts from complexity science for emergency and crisis management, to the evolution of NRP/NRF from the earlier FRP. The article uses the network analysis method in evaluating changes from FRP to NRF. The network analysis results demonstrate increases in complexity in the disaster and crises response and recovery plans over time.
105 citations
Posted Content•
TL;DR: In this article, a complex adaptive system for modeling financial markets is surveyed and compared with the autocorrelation patterns of returns, squared returns and absolute returns of 40 years of S&P 500 data.
Abstract: Recent work on complex adaptive systems for modeling financialmarkets is surveyed. Financia1 markets areviewed as evolutionary systems between different, competing tradingstrategies. Agents are boundedly rational inthe sense that they tend to follow strategies that have performedwell, according to realized profits or accumulatedwea1th, in the recent past. Simple technical trading rules maysurvive evolutionary competition in a heterogeneousworld where prices and beliefs co-evolve over time. The evolutionarymodel explains stylized facts, such as fat tails,volatility clustering and long memory, of real financial series.Although our adaptive belief systems are very simple, they can matchthe autocorrelation patterns of returns,squared returns and absolute returns of 40 years of S&P 500 data"Some recent laboratory work on expectationsformation in an asset pricing framework is also discussed.
103 citations
TL;DR: This paper presents an example of how an empirically-grounded, complexity-aware ToC can be developed and what such a model might look like in the context of a particular type of program intervention, and derives a “complexity-aware” ToC to model how the cases worked.
103 citations