7,345 research outputs found
Approximated Computation of Belief Functions for Robust Design Optimization
This paper presents some ideas to reduce the computational cost of
evidence-based robust design optimization. Evidence Theory crystallizes both
the aleatory and epistemic uncertainties in the design parameters, providing
two quantitative measures, Belief and Plausibility, of the credibility of the
computed value of the design budgets. The paper proposes some techniques to
compute an approximation of Belief and Plausibility at a cost that is a
fraction of the one required for an accurate calculation of the two values.
Some simple test cases will show how the proposed techniques scale with the
dimension of the problem. Finally a simple example of spacecraft system design
is presented.Comment: AIAA-2012-1932 14th AIAA Non-Deterministic Approaches Conference.
23-26 April 2012 Sheraton Waikiki, Honolulu, Hawai
Self-adaptive exploration in evolutionary search
We address a primary question of computational as well as biological research
on evolution: How can an exploration strategy adapt in such a way as to exploit
the information gained about the problem at hand? We first introduce an
integrated formalism of evolutionary search which provides a unified view on
different specific approaches. On this basis we discuss the implications of
indirect modeling (via a ``genotype-phenotype mapping'') on the exploration
strategy. Notions such as modularity, pleiotropy and functional phenotypic
complex are discussed as implications. Then, rigorously reflecting the notion
of self-adaptability, we introduce a new definition that captures
self-adaptability of exploration: different genotypes that map to the same
phenotype may represent (also topologically) different exploration strategies;
self-adaptability requires a variation of exploration strategies along such a
``neutral space''. By this definition, the concept of neutrality becomes a
central concern of this paper. Finally, we present examples of these concepts:
For a specific grammar-type encoding, we observe a large variability of
exploration strategies for a fixed phenotype, and a self-adaptive drift towards
short representations with highly structured exploration strategy that matches
the ``problem's structure''.Comment: 24 pages, 5 figure
- β¦