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- Title
- Achieving consistent evolution across isometrically equivalent search spaces
- Creator
- Patton, Arnold L.
- Date
- 2004
- Collection
- Electronic Theses & Dissertations
- Title
- Design automation of mechatronic systems using evolutionary computation and bond graph
- Creator
- Fan, Zhun
- Date
- 2004
- Collection
- Electronic Theses & Dissertations
- Title
- Enhancing pattern recognition using evolutionary computation for feature selection and extraction with application to the biochemistry of protein-water binding
- Creator
- Raymer, Michael L.
- Date
- 2000
- Collection
- Electronic Theses & Dissertations
- Title
- Evolving artificial neural networks with generative encodings inspired by developmental biology
- Creator
- Clune, Jeff
- Date
- 2010
- Collection
- Electronic Theses & Dissertations
- Title
- Harnessing evolutionary computation for the design and generation of adaptive embedded controllers within the context of uncertainty
- Creator
- Byers, Chad Michael
- Date
- 2015
- Collection
- Electronic Theses & Dissertations
- Description
-
A critical challenge for the design of embedded controllers is incorporating desirable qualities such as robustness, fault tolerance, and adaptability into the control process in order to respond to dynamic environmental conditions. An embedded controller governs the execution of a task-specific system by monitoring information from its environment via sensors and producing an appropriate response through the system's actuators, often independent of any supervisory control. For a human...
Show moreA critical challenge for the design of embedded controllers is incorporating desirable qualities such as robustness, fault tolerance, and adaptability into the control process in order to respond to dynamic environmental conditions. An embedded controller governs the execution of a task-specific system by monitoring information from its environment via sensors and producing an appropriate response through the system's actuators, often independent of any supervisory control. For a human developer, identifying the set of all possible combinations of conditions a system might experience and designing a solution to accommodate this set is burdensome, costly, and often, infeasible. To alleviate this burden, a variety of techniques have been explored to automate the generation of embedded controller solutions. In this dissertation, we focus on the bio-inspired technique referred to as evolutionary computation where we harness evolution's power as a population-based, global search technique to build up good behavioral components. In this way, evolution naturally selects for these desirable qualities in order for a solution to remain competitive over time in the population. Often, these search techniques operate in the context of uncertainty where aspects of the (1) problem domain, (2) solution space, and (3) search process itself are subject to variation and change. To mitigate issues associated with uncertainty in the problem domain, we propose the digital enzyme, a biologically-inspired model that maps the complexity of both the environment and the system into the space of values rather than instructions. To address uncertainty in the solution space, we remove constraints in our initial digital enzyme model to allow the genome structure to be dynamic and open-ended, accommodating a wider range of evolved solution designs. Finally, to help explore the inherent uncertainty that exists in the search process, we uncover a hidden feature interaction present between the diversity-preserving search operator of a popular evolutionary algorithm and propose a new way to use niching as a means to mitigate its unwanted effects and bias on search.
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- Title
- Natural niching : applying ecological principles to evolutionary computation
- Creator
- Goings, Sherri
- Date
- 2010
- Collection
- Electronic Theses & Dissertations
- Title
- Sustainable evolutionary algorithms and scalable evolutionary synthesis of dynamic systems
- Creator
- Hu, Jianjun
- Date
- 2004
- Collection
- Electronic Theses & Dissertations
- Title
- Using evolutionary approach to optimize and model multi-scenario, multi-objective fault-tolerant problems
- Creator
- Zhu, Ling (Engineer)
- Date
- 2017
- Collection
- Electronic Theses & Dissertations
- Description
-
Fault-tolerant design involves different scenarios, such as scenarios with no fault in the system, with faults occurring randomly, with different operation conditions, and with different loading conditions. For each scenario, there can be multiple requirements (objectives). To assess the performance of a design (solution), it needs to be evaluated over a number of different scenarios containing various requirements in each scenario. We consider this problem as a multi-scenario, multi...
Show moreFault-tolerant design involves different scenarios, such as scenarios with no fault in the system, with faults occurring randomly, with different operation conditions, and with different loading conditions. For each scenario, there can be multiple requirements (objectives). To assess the performance of a design (solution), it needs to be evaluated over a number of different scenarios containing various requirements in each scenario. We consider this problem as a multi-scenario, multi-objective (MSMO) problem.Despite its practical importance and prevalence in engineering application, there are not many studies which systematically solve the MSMO problem. In this dissertation, we focus on optimizing and modeling MSMO problems, and propose various approaches to solve different types of MSMO optimization problems, especially multi-objective fault-tolerant problems. We classify MSMO optimization problem into two categories: scenario-dependent and scenario-independent. For the scenario-dependent MSMO problem, we review existing methodologies and suggest two evolutionary-based methods for handling multiple scenarios and objectives: aggregated method and integrated method. The effectiveness of both methods are demonstrated on several case studies including numerical problems and engineering design problems. The engineering problems include cantilever-type welded beam design, truss bridge design, four-bar truss design. The experimental results show that both methods can find a set of widely distributed solutions that are compromised among the respective objective values under all scenarios. We also model fault-tolerant programs using the aggregated method. We synthesize three fault-tolerant distributed programs: Byzantine agreement program, token ring circulation program and consensus program with failure detector $S$. The results show that evolutionary-base MSMO approach, as a generic method, can effectively model fault-tolerant programs. For the scenario-independent MSMO problem, we apply evolutionary multi-objective approach. As a case study, we optimize a probabilistic self-stabilizing program, a special type of fault-tolerant program, and obtain several interesting counter-intuitive observations under different scenarios.
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- Title
- Using evolutionary computation to automatically refractor software designs to include design patterns
- Creator
- Jensen, Adam C.
- Date
- 2010
- Collection
- Electronic Theses & Dissertations