Routing in Congestible Networks

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Networks form the infrastructure for the functioning of modern societies and economies. In particular, transportation networks allow for the move of commuters, mail, and material goods, and communication networks (e.g., Internet) accomplish the same for the transmission of information. When users independently choose their routes in the network, their objective is to minimize their costs (measured in time, money, or energy) without explicitly considering the negative externalities they impose on others. Almost inevitably, over time the demand placed on the network, its topology, or both undergo changes. We do not know if and how network users, who are bounded rationality, susceptible to various biases, and who may not coordinate their decisions, adapt to these changes by choosing new routes. In this research, the PIs will systematically manipulate network structure in an experimental setting to learn how highly motivated network users - human subjects who volunteer to take part in network experiments for payment contingent on their performance - react to these changes.To achieve this purpose, six projects will be undertaken. The theoretical benchmark that drives the investigation is the Nash equilibrium solution concept of game theory. Under this solution, each strategy chosen by any member of the population is a best response to the strategy choices of the other members. The PIs will construct complex networks in a computer-controlled laboratory with multiple routes connecting pre-designated origins to pre-designated destinations, derive the equilibrium solutions for these networks, display them on computer screens, and ask subjects to independently choose routes that minimize their individual cost. The patterns of behavior elicited will then be compared with the Nash equilibrium predictions before and after manipulation of the network, deviations from equilibrium play, if any, will be identified and accounted for using new theories based on concepts and ideas from economics, psychology, and organization science. In terms of broader signficance, the findings from these studies will be useful for planning the expansion of networks to meet changes in demand or in the structure of the network, for increasing efficiency in networks, and for determining what information on network conditions to display on-line to network users.