[hpc-announce] Call for Papers: Workshop on Evolutionary Computation and CBR
Andrew M Sutton
amsutton at d.umn.edu
Mon Apr 23 17:21:59 CDT 2018
** EvoCBR 2018: Workshop on Evolutionary Computation and CBR **
Call for Papers:
Genetic Algorithms and Evolutionary Computation are effective
techniques, for achieving optimal or near optimal solutions which have
gained explicit attention of researchers over the last decade, and is
still growing each year. Many current research areas in Case-Based
Reasoning such as case adaptation, feature selection, feature weight
selection, and case injection among others can be solved using
optimization techniques. However, despite work combining these two
algorithms since the early 1990’s, cross communication and collaboration
between the two areas has diminished. This workshop is dedicated to the
interplay between Evolutionary Computations and CBR. The goal of this
workshop is to foster communication between researchers in these two
areas and provide a forum to identify opportunities and challenges in
both Evolutionary Computation and CBR which can be solved using each other.
We are looking for methods and techniques that exploit evolutionary
computation for the benefit of Case-based reasoning (CBR) or vice versa.
We particularly welcome contributions in areas that include, but are not
limited to, the following:
* Hybrid Evolutionary Computation/CBR systems.
* Similarity function optimization using Evolutionary Computation
* Feature Selection using Evolutionary Computations
* Theoretical aspects of Evolutionary Computations and CBR.
* Evolutionary Computation for case adaptation.
* Evolutionary Computation in Case-Based Retrieval.
* Evolutionary Computation in Case-Based Reuse.
* Evolutionary Computation in Case-Based Revise.
* Evolutionary Computation in Case-Based Retain
* Evolutionary Computation in Case-Based creation.
* Applications that perform Evolutionary Computation and CBR.
* Nature-inspired algorithms and CBR.
We encourage everyone to make the research presented at this workshop
reproducible. This means making the source code, the data and the
experiments available to the workshop participants specifically and
research community in general if possible. This is not required, only
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