Matching Items (11)
Description
The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.
ContributorsHaghnevis, Moeed (Author) / Askin, Ronald G. (Thesis advisor) / Armbruster, Dieter (Thesis advisor) / Mirchandani, Pitu (Committee member) / Wu, Tong (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation investigates the long-term consequences of human land-use practices in general, and in early agricultural villages in specific. This pioneering case study investigates the "collapse" of the Early (Pre-Pottery) Neolithic lifeway, which was a major transformational event marked by significant changes in settlement patterns, material culture, and social markers. To move beyond traditional narratives of cultural collapse, I employ a Complex Adaptive Systems approach to this research, and combine agent-based computer simulations of Neolithic land-use with dynamic and spatially-explicit GIS-based environmental models to conduct experiments into long-term trajectories of different potential Neolithic socio-environmental systems. My analysis outlines how the Early Neolithic "collapse" was likely instigated by a non-linear sequence of events, and that it would have been impossible for Neolithic peoples to recognize the long-term outcome of their actions. The experiment-based simulation approach shows that, starting from the same initial conditions, complex combinations of feedback amplification, stochasticity, responses to internal and external stimuli, and the accumulation of incremental changes to the socio-natural landscape, can lead to widely divergent outcomes over time. Thus, rather than being an inevitable consequence of specific Neolithic land-use choices, the "catastrophic" transformation at the end of the Early Neolithic was an emergent property of the Early Neolithic socio-natural system itself, and thus likely not an easily predictable event. In this way, my work uses the technique of simulation modeling to connect CAS theory with the archaeological and geoarchaeological record to help better understand the causes and consequences of socio-ecological transformation at a regional scale. The research is broadly applicable to other archaeological cases of resilience and collapse, and is truly interdisciplinary in that it draws on fields such as geomorphology, computer science, and agronomy in addition to archaeology.
ContributorsUllah, Isaac (Author) / Barton, C. Michael (Thesis advisor) / Banning, Edward B. (Committee member) / Clark, Geoffrey (Committee member) / Arrowsmith, J. Ramon (Committee member) / Arizona State University (Publisher)
Created2013
Description
Design is a fundamental human activity through which we attempt to navigate and manipulate the world around us for our survival, pleasure, and benefit. As human society has evolved, so too has the complexity and impact of our design activities on the environment. Now clearly intertwined as a complex social-ecological system at the global scale, we struggle in our ability to understand, design, implement, and manage solutions to complex global issues such as climate change, water scarcity, food security, and natural disasters. Some have asserted that this is because complex adaptive systems, like these, are moving targets that are only partially designed and partially emergent and self-organizing. Furthermore, these types of systems are difficult to understand and control due to the inherent dynamics of "wicked problems", such as: uncertainty, social dilemmas, inequities, and trade-offs involving multiple feedback loops that sometimes cause both the problems and their potential solutions to shift and evolve together. These problems do not, however, negate our collective need to effectively design, produce, and implement strategies that allow us to appropriate, distribute, manage and sustain the resources on which we depend. Design, however, is not well understood in the context of complex adaptive systems involving common-pool resources. In addition, the relationship between our attempts at control and performance at the system-level over time is not well understood either. This research contributes to our understanding of design in common-pool resource systems by using a multi-methods approach to investigate longitudinal data on an innovative participatory design intervention implemented in nineteen small-scale, farmer-managed irrigation systems in the Indrawati River Basin of Nepal over the last three decades. The intervention was intended as an experiment in using participatory planning, design and construction processes to increase food security and strengthen the self-sufficiency and self-governing capacity of resource user groups within the poorest district in Nepal. This work is the first time that theories of participatory design-processes have been empirically tested against longitudinal data on a number of small-scale, locally managed common-pool resource systems. It clarifies and helps to develop a theory of design in this setting for both scientific and practical purposes.
ContributorsRatajczyk, Elicia Beth (Author) / Anderies, John M (Thesis advisor) / York, Abigail (Committee member) / Shivakoti, Ganesh P (Committee member) / Arizona State University (Publisher)
Created2018
Description
Pressure from fiduciary duty leads agents within organizational systems to make decisions that result in positive feedback loops that often have inimical unintended consequences. The current corporate climate that often puts the bottom line ahead of environmental and social concerns in the name of fiduciary duty is doing so based on a revised interpretation of the term that is clearly to the benefit of the corporations. It is important to note that this modern interpretation is a radical misinterpretation of the intent of the law as our forefathers defined it. However, in spite of the fact that the modern interpretation is leading to inimical unintended consequences, providing the systems agents with the proper training and tools necessary to recognize the cost benefit of implementing sustainable solutions may mitigate some of these positive feedback loops and their associated unintended consequences. By developing tools based on sustainable frameworks we may be able to return these organizations to the original intent of fiduciary duty, which was designed to encourage investment in organizations that worked for the public benefit. A concept that is remarkably similar to the triple bottom line framework that many sustainability professionals advocate on behalf of today.
ContributorsJohnson, Lyle Eric (Author) / Laubichler, Manfred (Thesis director) / Dooley, Kevin (Committee member) / O'Neill, Dan (Committee member) / Barrett, The Honors College (Contributor) / W. P. Carey School of Business (Contributor) / School of Sustainability (Contributor)
Created2015-05
Description
Unmanned aerial vehicles have received increased attention in the last decade due to their versatility, as well as the availability of inexpensive sensors (e.g. GPS, IMU) for their navigation and control. Multirotor vehicles, specifically quadrotors, have formed a fast growing field in robotics, with the range of applications spanning from surveil- lance and reconnaissance to agriculture and large area mapping. Although in most applications single quadrotors are used, there is an increasing interest in architectures controlling multiple quadrotors executing a collaborative task. This thesis introduces a new concept of control involving more than one quadrotors, according to which two quadrotors can be physically coupled in mid-flight. This concept equips the quadro- tors with new capabilities, e.g. increased payload or pursuit and capturing of other quadrotors. A comprehensive simulation of the approach is built to simulate coupled quadrotors. The dynamics and modeling of the coupled system is presented together with a discussion regarding the coupling mechanism, impact modeling and additional considerations that have been investigated. Simulation results are presented for cases of static coupling as well as enemy quadrotor pursuit and capture, together with an analysis of control methodology and gain tuning. Practical implementations are introduced as results show the feasibility of this design.
ContributorsLarsson, Daniel (Author) / Artemiadis, Panagiotis (Thesis advisor) / Marvi, Hamidreza (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2016
Description
The Department of Defense (DoD) acquisition system is a complex system riddled with cost and schedule overruns. These cost and schedule overruns are very serious issues as the acquisition system is responsible for aiding U.S. warfighters. Hence, if the acquisition process is failing that could be a potential threat to our nation's security. Furthermore, the DoD acquisition system is responsible for proper allocation of billions of taxpayer's dollars and employs many civilians and military personnel. Much research has been done in the past on the acquisition system with little impact or success. One reason for this lack of success in improving the system is the lack of accurate models to test theories. This research is a continuation of the effort on the Enterprise Requirements and Acquisition Model (ERAM), a discrete event simulation modeling research on DoD acquisition system. We propose to extend ERAM using agent-based simulation principles due to the many interactions among the subsystems of the acquisition system. We initially identify ten sub models needed to simulate the acquisition system. This research focuses on three sub models related to the budget of acquisition programs. In this thesis, we present the data collection, data analysis, initial implementation, and initial validation needed to facilitate these sub models and lay the groundwork for a full agent-based simulation of the DoD acquisition system.
ContributorsBucknell, Sophia Robin (Author) / Wu, Teresa (Thesis director) / Li, Jing (Committee member) / Colombi, John (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Variation in living systems and how it cascades across organizational levels is central to biology. To understand the constraints and amplifications of variation in collective systems, I mathematically study how group-level differences emerge from individual variation in eusocial-insect colonies, which are inherently diverse and easily observable individually and collectively. Considering collective processes in three species where increasing degrees of heterogeneity are relevant, I address how individual variation scales to colony-level variation and to what degree it is adaptive. In Chapter 2, I introduce a Markov-chain decision model for stochastic individual quorum-based recruitment decisions of rock-ant workers during house hunting, and how they determine collective speed--accuracy balance. Differences in the average threshold-dependent response characteristics of workers between colonies cause collective differences in decision-making. Moreover, noisy behavior may prevent drastic collective cascading into poor nests. In Chapter 3, I develop an ordinary differential equation (ODE) model to study how cognitive diversity among honey-bee foragers influences collective attention allocation between novel and familiar resources. Results provide a mechanistic basis for changes in foraging activity and preference with group composition. Moreover, sensitivity analysis reveals that the main individual driver for foraging allocation shifts from recruitment (communication) to persistence (independent effort) as colony composition changes. This might favor specific degrees of heterogeneity that best amplify communication in wild colonies. Lastly, in Chapter 4, I consider diversity in size, age, and task for nest defense in stingless bees. To better understand how these dimensions of diversity interact to balance defensive demands with other colony needs, I study their effect on colony size and task allocation through a demographic Filippov ODE model. Along each dimension, variation is beneficial in a certain range, outside of which colony adaptation and survival are compromised. This work elucidates how variation in collective properties emerges from nonlinear interactions between varying components in eusocial insects, but it can be generalized to other biological systems with similar fundamental characteristics but less empirical tractability. Moreover, it has the potential of inspiring algorithms that capitalize on heterogeneity in engineered systems where simple components with limited information and no central control must solve complex tasks.
ContributorsNavas Zuloaga, Maria Gabriela (Author) / Kang, Yun (Thesis advisor) / Smith, Brian H (Thesis advisor) / Pavlic, Theodore P (Committee member) / Arizona State University (Publisher)
Created2022
Description
This dissertation explores how practices and interactions of actors at different scales structure social networks and lead to the emergence of social complexity in middle range societies. To investigate this process, I apply a complex adaptive systems approach and a methodology that combines network science with analytical tools from economics to the three sub-periods of the Prehistoric Bronze Age (The Philia Phase, PreBA 1 and PreBA 2) on Cyprus, a transformational period marked by social and economic changes evident in the material record. Using proxy data representative of three kinds of social interactions or facets of social complexity, the control of labor, participation in trade networks, and access to resources, at three scales, the community, region and whole island, my analysis demonstrates the variability in and non-linear trajectory for the emergence of social complexity in middle range society. The results of this research indicate that complexity emerges at different scales, and times in different places, and only in some facets of complexity. Cycles of emergence are apparent within the sub-periods of the PreBA, but a linear trajectory of increasing social complexity is not evident through the period. Further, this research challenges the long-held notion that Cyprus' involvement in the international metal trade lead to the emergence of complexity. Instead, I argue based on the results presented here, that the emergence of complexity is heavily influenced by endogenous processes, particularly the social interactions that limited participation in an on-island exchange system that flourished on the island during the Philia Phase, disintegrated along the North Coast during the PreBA 1 and was rebuilt across the island by the end of the period. Thus, the variation seen in the emergence of social complexity on Cyprus during the PreBA occurred as the result of a bottom-up process in which the complex and unequal interactions and relationships between social actors structured and restructured social networks across scales differently over time and space. These results speak more broadly about the variability of middle range societies and the varying conditions under which social complexity can emerge and add to our understanding of this phenomenon.
ContributorsSwantek, Laura Anne (Author) / Barton, C. Michael (Thesis advisor) / Spielmann, Katherine (Committee member) / Serwint, Nancy (Committee member) / Arizona State University (Publisher)
Created2017
Description
There has been a vast increase in applications of Unmanned Aerial Vehicles (UAVs) in civilian domains. To operate in the civilian airspace, a UAV must be able to sense and avoid both static and moving obstacles for flight safety. While indoor and low-altitude environments are mainly occupied by static obstacles, risks in space of higher altitude primarily come from moving obstacles such as other aircraft or flying vehicles in the airspace. Therefore, the ability to avoid moving obstacles becomes a necessity
for Unmanned Aerial Vehicles.
Towards enabling a UAV to autonomously sense and avoid moving obstacles, this thesis makes the following contributions. Initially, an image-based reactive motion planner is developed for a quadrotor to avoid a fast approaching obstacle. Furthermore, A Dubin’s curve based geometry method is developed as a global path planner for a fixed-wing UAV to avoid collisions with aircraft. The image-based method is unable to produce an optimal path and the geometry method uses a simplified UAV model. To compensate
these two disadvantages, a series of algorithms built upon the Closed-Loop Rapid Exploratory Random Tree are developed as global path planners to generate collision avoidance paths in real time. The algorithms are validated in Software-In-the-Loop (SITL) and Hardware-In-the-Loop (HIL) simulations using a fixed-wing UAV model and in real flight experiments using quadrotors. It is observed that the algorithm enables a UAV to avoid moving obstacles approaching to it with different directions and speeds.
for Unmanned Aerial Vehicles.
Towards enabling a UAV to autonomously sense and avoid moving obstacles, this thesis makes the following contributions. Initially, an image-based reactive motion planner is developed for a quadrotor to avoid a fast approaching obstacle. Furthermore, A Dubin’s curve based geometry method is developed as a global path planner for a fixed-wing UAV to avoid collisions with aircraft. The image-based method is unable to produce an optimal path and the geometry method uses a simplified UAV model. To compensate
these two disadvantages, a series of algorithms built upon the Closed-Loop Rapid Exploratory Random Tree are developed as global path planners to generate collision avoidance paths in real time. The algorithms are validated in Software-In-the-Loop (SITL) and Hardware-In-the-Loop (HIL) simulations using a fixed-wing UAV model and in real flight experiments using quadrotors. It is observed that the algorithm enables a UAV to avoid moving obstacles approaching to it with different directions and speeds.
ContributorsLin, Yucong (Author) / Saripalli, Srikanth (Thesis advisor) / Scowen, Paul (Committee member) / Fainekos, Georgios (Committee member) / Thangavelautham, Jekanthan (Committee member) / Youngbull, Cody (Committee member) / Arizona State University (Publisher)
Created2015
Description
Energy poverty is pervasive in sub-Saharan Africa. Nigeria, located in sub-Saharan West Africa, is the world's seventh largest oil exporting country and is a resource-rich nation. It however experiences the same levels of energy poverty as most of its neighboring countries. Attributing this paradox only to corruption or the "Dutch Disease", where one sector booms at the expense of other sectors of the economy, is simplistic and enervates attempts at reform. In addition, data on energy consumption is aggregated at the national level via estimates, disaggregated data is virtually non-existent. Finally, the wave of decentralization of vertically integrated national utilities sweeping the developing world has caught on in sub-Saharan Africa. However, little is known of the economic and social implications of these transitions within the unique socio-technical system of the region's electricity sector, especially as it applies to energy poverty. This dissertation proposes a complex systems approach to measuring and mitigating energy poverty in Nigeria due to its multi-dimensional nature. This is done via a three-fold approach: the first section of the study delves into causation by examining the governance institutions that create and perpetuate energy poverty; the next section proposes a context-specific minimum energy poverty line based on field data collected on energy consumption; and the paper concludes with an indicator-based transition management framework encompassing institutional, economic, social, and environmental themes of sustainable transition within the electricity sector. This work contributes to intellectual discourse on systems-based mitigation strategies for energy poverty that are widely applicable within the sub-Saharan region, as well as adds to the knowledge-base of decision-support tools for addressing energy poverty in its complexity.
ContributorsChidebell Emordi, Chukwunonso (Author) / York, Abigail (Thesis advisor) / Pasqualetti, Martin (Committee member) / Golub, Aaron (Committee member) / Arizona State University (Publisher)
Created2015