Constraints (2014) 19:174–185 DOI 10.1007/s10601-014-9161-y Strategic decision making on complex systems Michela Milano · Michele Lombardi Published online: 9 March 2014 © Springer Science+Business Media New York 2014 Abstract In this paper, we propose a challenging research direction for Constraint Pro- gramming and optimization techniques in general. We address problems where decisions to be taken affect and are affected by complex systems, which exhibit phenomena emerging from a collection of interacting objects, capable to self organize and to adapt their behaviour according to their history and feedback. Such systems are unfortunately impervious to mod- eling efforts via state-of-the-art combinatorial optimization techniques. We provide some hints on approaches to connect and integrate decision making and optimization technology with complex systems via machine learning, game theory and mechanism design. In the first case, the aim is to extract modeling components to express the relation between global decisions and observables emerging from the real system, or from an accurate predictive model (e.g. a simulator). In the second case, the idea is to exploit game theory, mechanism design and distributed decision making to drive the process toward realistic equilibrium points avoiding globally optimal, but unrealistic, configurations. We conclude by observing how dealing with the complexity of the considered problems will require to greatly extend the capabilities of state of the art solvers: in this context, we identify some key issues and highlight future research directions. Keywords Combinatorial optimization · Complex systems · Constraint programming · Machine learning · Simulation · Game theory · Hybrid optimization · Large scale problems 1 Introduction Combinatorial decision making and optimization technology has achieved a good level of maturity in the last decades. A number of different approaches have been defined to M. Milano · M. Lombardi () DISI, University of Bologna, V.le Risorgimento 2, 40136 Bologna, Italy e-mail: michele.lombardi2@unibo.it M. Milano e-mail: michela.milano@unibo.it