text-only page produced automatically by LIFT Text
Transcoder Skip all navigation and go to page contentSkip top navigation and go to directorate navigationSkip top navigation and go to page navigation
National Science Foundation HomeNational Science Foundation - Directorate for Computer & Information Science & Engineering (CISE)
Computing & Communication Foundations (CCF)
design element
CCF Home
About CCF
Funding Opportunities
Awards
News
Events
Discoveries
Publications
Career Opportunities
View CCF Staff
CISE Organizations
Advanced Cyberinfrastructure (ACI)
Computing and Communication Foundations (CCF)
Computer and Network Systems (CNS)
Information & Intelligent Systems (IIS)
Proposals and Awards
Proposal and Award Policies and Procedures Guide
  Introduction
Proposal Preparation and Submission
bullet Grant Proposal Guide
  bullet Grants.gov Application Guide
Award and Administration
bullet Award and Administration Guide
Award Conditions
Other Types of Proposals
Merit Review
NSF Outreach
Policy Office


CISE - CCF

INTERFACE BETWEEN COMPUTER SCIENCE AND ECONOMICS & SOCIAL SCIENCE (ICES)

Following are several illustrations of the kinds of research this program seeks to support. They are illustrative only and research in new and innovative application areas is also encouraged. We have organized them in two categories.

  1. Algorithmic approaches and analyses for social science questions involving resource provision and allocation in noisy, distributed and/or unsynchronized environments, collective decision making, and related topics, including, but not limited to:
    • What is the nature of equilibrium prices in a network of buyers and sellers?
    • How can we set up computationally efficient mechanisms that achieve one or more desirable technical and/or policy objectives?
    • How do networks of economic agents form and evolve? How do we model and study the effect of non-economic constraints (e.g., regulatory, legal, institutional, or ethical) on the network?
    • New markets have been and continue to be created in socio-technical networks, some involving billions of dollars' worth of transactions. How do these markets relate to well-studied existing markets? How can computational and algorithmic innovations enable, analyze and/or predict emerging market paradigms?
    • How do agents (human or machine) in a network learn and adapt dynamically, especially in response to incentives?
    • How does information spread in a network of self-interested agents and how can contagion be enhanced or reduced? What is the computational complexity of strategic equilibrium, and what state is reached when this computation is intractable?
    • How can we understand the increasingly complex and flexible decision and choice systems made possible by modern computer systems? This includes markets, voting, recommender systems, and recommendation systems.
  2. Mechanisms that use ideas from social and economic science to improve the performance of computing systems and other systems of multiple, self-interested agents, including, but not limited to:
    • How can we regulate traffic on the Internet using economic incentives?
    • How can economic approaches be used to optimize any of several quantities of interest such as network utilization, congestion minimization, latency, throughput, etc.? A central problem is to induce providers to reveal their true best options, which may not be in their best interests.
    • How can we disincentivize or otherwise discourage spam, malware, and other misuse of networked socio-technical systems?
    • How can we create stable and truthful reputation systems, voting systems, and other social mechanisms for gathering information about the preferences of individuals?
    • How can we model vandals, spammers, hackers, identity thieves, terrorists, etc. as self-interested agents and build trust and security in networks against such adversaries?
    • Can we incentivize the adoption of better mechanisms (for instance, for security or resource allocation) that require widespread adoption before they become effective?

 

Email this pagePrint this page
Back to Top of page