In the last years, many contributions have been exploring population learning in economies where myopic agents play bilateral games and are allowed to repeatedly choose their pure strategies in the game and, possibly, their opponents in the game. These models explore bilateral stage-games...

Population learning in dynamic economies has been traditionally studied in over-simplified settings where payoff landscapes are very smooth. Indeed, in these models, all agents play the same bilateral stage-game against any opponent and stage-game payoffs reflect very simple strategic situations...

In the last years, many contributions have been exploring population learning in economies where myopic agents play bilateral games and are allowed to repeatedly choose their pure strategies in the game and, possibly, their opponents in the game. These models explore bilateral stage-games...

In many complex systems control situations, searching for solutions or alternatives is involved. Searching for solutions can be modeled by a search on a fitness landscape. Knowing the structure of the underlying landscape can help in explaining or predicting aspects of an actual seach on it, and...

Choice settings are strategic to the extent that they entail cross-sectional or intertemporal linkages. These same factors may impose daunting demands on decision makers. We develop a graph-theoretic generalization of the NK model of fitness landscapes to model the way in which policy choices...

Population learning in dynamic economies traditionally has been studied in contexts where payoff landscapes are smooth. Here, dynamic population games take place over “rugged” landscapes, where agents are uncertain about payoffs from bilateral interactions. Notably, individual payoffs from...