Initial offer magnitude 10. Strategic postures Different variants of agents were created based on various combinations of the above factors. For example, a rational agent is fully aware of opponent preferences. The prototype was able to predict and manifest several aspects of individual and dyadic behavior. Most of the predictions were consistent with results documented in the general literature.
Conclusions Distributed decision processes involve complex agent interactions.
The ability to generate such non-linear behavior might help us to understand aspects such as evolving strategies, shifting preferences, and coalition formations. We have presented a new approach which is a paradigm shift from the way researchers have studied distributed processes. The prototype used in this study represents each agent decision process as an adaptive search procedure. Simulation experiments reveal that it is able to generate fundamental patterns that have been documented in the literature. A validated computational model could serve as an artificial laboratory environment for analyzing and studying the separate or joint impact of different variables.