Interface Between Computer Science and Economics and Social Science(s):
National Science Foundation (NSF)
Deadline: October 5, 2010
The histories and intellectual approaches of social and economic science and computer science have been strongly
influenced by the crosscurrents among them. Game theory is widely used in social and economic science. Social and
economic scientists use concepts that are linked to computer science. For example, decision scientists and economists
consider the bounded rationality of individuals making economic decisions; one aspect of bounded rationality is that
economic agents may be limited by their "computational" resources, for example in evaluating complicated strategic
The ubiquity of socio-technical networks has led to new, more intimate ties between these two fields. New kinds of
interactions and transactions have been enabled by such networks. Key features of these new transactions include: parties
who do not know or trust each other; parties represented by software agents; real-time adaptation, decision making,
and chain reactions by agents.
Designing decision mechanisms that can govern these increasingly important types of transactions in ways that
meet criteria such as fairness, revenue maximization, or efficient resource use is a challenge that requires the expertise
of both social and economic scientists and computer scientists.
Internet traffic (as also physical traffic on our road networks), email, the use of network bandwidth, the allocation of
computing resources to competing processes, etc., may be managed using economic and social choice mechanisms to
achieve better utilization and reduction of the nuisance and harm caused by intruders and spammers. Good incentive
mechanisms are also needed to mediate the interactions among infrastructure providers, service providers, and clients
for computing and communication infrastructure. Mechanisms are also important in driving multi-agent software systems
towards socially desirable goals. These questions may require a new understanding of simultaneous collaboration
and competition among economic agents.
Computational thinking has the potential to change the types of questions considered by social and economic scientists.
Computational thinking can help characterize the range and robustness of possible equilibria and markets for
which the computation of equilibria is intractable. Theories of strategic learning by computational agents, studied both
in economics and computer science, can shed light on the dynamics of how agents arrive at equilibria. Theories of the
spread of contagion or gossip in networks can help explain and contain the chain reactions that can arise. Social/
behavioral/economic and computer scientists can jointly study the dynamic functioning and evolution of social and economic
networks with mutual benefit to both fields of study.
This program seeks innovative research at this interdisciplinary boundary, including both projects that use computational
thinking for economic and social decision problems and/or ideas from economics and other social sciences for
computing and communication systems and multi-agents systems. Computational economics research involving simulation
and modeling of economic systems is not appropriate for this program.
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