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approach makes it easier to identify different local optima using sampling mechanisms. In stochastic optimization, distribution estimation algorithms (EDA) are an alternative approach to traditional
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: Develop and apply evolutionary algorithms to jointly optimize both the robot’s morphology and autonomy, and apply quality-diversity methods to discover a wide range of high-performing designs. Work
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of the candidate and the needs of the research center. More specifically, the postdoc will work on the following topics, in collaboration with the rest of the team: Develop and apply evolutionary algorithms
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for creative or artistic purposes PhD thesis relevant to the research described in MishMash WP1 Experience with AI methods/algorithms such as evolutionary and quality-diversity search, generative ML models
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-inspired selection). 3-Investigate the integration of QIEC with Quality-Diversity (QD) algorithms such as MAP-Elites.(month 2-3) 4-Explore the use of Evolutionary Computation to generate and optimize quantum
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methods/algorithms such as evolutionary and quality-diversity search, generative ML models, hybrid models, bio-inspired approaches, multi-agent systems Experience with real-time or embedded systems