Abstract:
Historically, group behavior (networks, organizations) has been studied as an aggregate effect, where the unit of learning is the group rather than the individual, and learning phenomena observed at the group level (e.g., exploration/exploitation, similarity effects) often resembles what is known from individual learning. We argue that all learning takes place inside individual human heads, and that group behavior emerges from individual strategies, the interdependence among individuals in a group, and the aggregation behavior of individuals in a group. In this talk I will discuss our efforts to demonstrate this premise. I will highlight results derived from experiments in 2-person games and the role of information regarding their interdependence on the individual and group behavior. I will also demonstrate how a cognitive model of individual learning based on Instance-Based Learning (IBL) Theory was expanded to account for group learning. Using IBL models, I will demonstrate effects of a taxonomy of payoff interdependence in 2-person interactions, and escalate those results to groups of various structures (e.g. fully connected, lattice networks). We find that mutually rewarding actions between members of a group emerge from individual selfishness when the payoff interdependence is conducive to mutually beneficial actions. We also find that the more connections there are in a group (e.g., fully connected network) the less likely it is that individuals will learn mutually rewarding actions.
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