This paper discusses the question whether self-learning price-setting algorithms are able to coordinate their pricing behaviour to achieve a collusive outcome that maximizes the joint profits of the firms using these algorithms. While the legal literature generally assumes that algorithmic...

Previous research has shown that opportunities for two-sided partner choice in finitely repeated social dilemma games can promote cooperation through a combination of sorting and opportunistic signaling, with late period defections by selfish players causing an end-game decline. How such...

Models with heterogeneous interacting agents explain macro phenomena through interactions at the micro level. We propose genetic algorithms as a model for individual expectations to explain aggregate market phenomena. The model explains all stylized facts observed in aggregate price fluctuations...

The need for efficient coordination is ubiquitous in organizations and industries. The literature on the determinants of efficient coordination has focused on individual decision making so far. In reality, however, teams often have to coordinate with other teams. We present a series of...

In this paper we introduce four new learning models: impulse balance learning, impulse matching learning, action-sampling learning, and payof-sampling learning. With this models and together with the models of self-tuning EWA learning and reinforcement learning, we conduct simulations over 12...