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.