EMOG 2015 - Special Session on Evolutionary Multiobjective Optimization and Games

When solving problems in the real world, we usually have to satisfy or optimize more than one
objective. These objectives, for example, minimizing time, cost, distance, storage, etc., are often
conflicting, which means that improvement on one objective value results in the degradation of
another. Instead of seeking for a single optimal solution with respect to one objective,
multiobjective optimization aims at seeking for the set of so-called Pareto optimal solutions.
Evolutionary algorithms, with its population-based nature, are suitable and have shown to be
effective for multiobjective optimization problems.
This special session aims to bring together experts in the field of evolutionary multiobjective
optimization (EMO) and experts in the field of games to discuss challenging issues and exchange
interesting ideas. We encourage submission of papers applying EMO techniques to deal with
multiobjective optimization problems encountered in games.
Topics of interest include, but are not limited to:
1. Formulation of multiobjective optimization problems in games
2. Applications of EMO algorithms to games
3. Performance comparison of EMO algorithms in games
4. Interactive EMO in games
5. EMO and constraint handling in games
6. EMO and dynamic/real-time/uncertain environments in games
7. EMO and parallelization in games
8. Many-objective optimization in games
9. Hybridization of EMO and other techniques (e.g. neural networks, Monte Carlo tree search,