Optimisation and machine learning tools are among the most used tools in the modern world due to their omnipresent computing devices. Yet, while both these tools rely on search processes (search for a solution or a model able to produce solutions), their dynamics have not been fully understood. Such scarcity of knowledge on the inner workings of heuristic methods is largely attributed to the complexity of the underlying processes that cannot be subjected to a complete theoretical analysis. However, this is also partially due to a superficial experimental setup and, therefore, a superficial interpretation of numerical results. Indeed, researchers and practitioners typically only look at the final result produced by these methods. Meanwhile, the vast amount of information collected over the run(s) is wasted. In light of such considerations, it is now becoming more evident that such information can be useful and that some design principles should be defined that allow for online or offline analysis of the processes taking place in the population and their dynamics.


Hence, with this workshop, we call for papers on both theoretical and empirical achievements identifying the desired features of optimisation and machine learning algorithms, quantifying the importance of such features, spotting the presence of intrinsic structural biases and other undesired algorithmic flaws, studying the transitions in algorithmic behaviour in terms of convergence, any-time behaviour, traditional and alternative performance measures, robustness, exploration vs exploitation balance, diversity, algorithmic complexity, etc., intending to gather the most recent advances to fill the aforementioned knowledge gap and disseminate the current state-of-the-art within the research community.

We encourage submissions that exploit carefully designed experiments or data-heavy approaches that can help analyse primary algorithmic behaviours and model the internal dynamics causing them.


ORGANIZING COMMITTEE
Anna V. Kononova - Leiden University, The Netherlands
Niki van Stein - Leiden University, The Netherlands
Thomas Bäck - Leiden University, The Netherlands
Daniela Zaharie - the West University of Timisoara, Romania
Fabio Caraffini - Swansea University, UK