Track Policies

Deployed Application Case Study Papers

Case-study papers must describe deployed applications with measurable benefits that include some aspect of AI technology. The application needs to have been in production use by their final endusers (typically for at least three months). The case study may evaluate either a stand-alone application or a component of a complex system. In addition to the criteria listed above for the Emerging Track papers, the deployed applications will also be evaluated on the following: task or problem description; application description; uses of AI technology; application use and payoff; application development and deployment; and maintenance.

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Emerging Application or Methodologies Papers

The goal of the emerging application track is to "bridge the gap" between basic AI research and deployed AI applications, by discussing efforts to apply AI tools, techniques, or methods to real world problems.

Emerging applications are on aspects of AI applications that are not appropriate for deployed application case studies, or are not sufficiently deployed to be submitted as case studies. This track is distinguished from reports of scientific AI research appropriate for the IJCAI-09 Conference in that the objective of the efforts reported here should be the engineering of AI applications.Emerging application papers may include any aspects of the technology, engineering, or deployment of AI applications, including discussions of prototype applications; performance evaluation of AI applications; ongoing efforts to develop large-scale or domain-specific knowledge bases or ontologies; development of domain or task focused tools, techniques, or methods; evaluations of AI tools, techniques or methods for domain suitability; unsuccessful attempts to apply particular tools, techniques or methods to specific domains (which shed insight on the applicability and limitations of the tool, technique or method); system architectures that work; scalability of techniques; integration of AI with other technologies; development methodologies; validation and verification; lessons learned; social and other technology transition issues.    

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AAAI / SIGART Doctoral Consortium

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