There is a long and fascinating history of humankind's endeavor to   
   explain and, with the advent of AI, ultimately mechanize the   
   overarching processes that lead to scientific discoveries. Over the   
   past 60 years, AI researchers have produced systems which have   
   generated novel and interesting conjectures (some which have spawned   
   new scientific research areas), and invented increasingly efficient   
   techniques to prove or refute them.   
      
   Nevertheless, the sobering fact remains that such advances fall short   
   of approaching the creativity and innovation of even amateur   
   scientists.  We believe that AI is ripe for revolutionary progress in   
   automated and semi-automated scientific discovery, in no small part   
   because the field now has on hand systems that mark advances in   
   various *parts* of discovery---parts that, when interconnected, may   
   make for exciting new systems.  We also believe that dialogue between   
   researchers behind these systems will lead to a new generation of   
   powerful AI discovery systems.   
      
   This symposium will survey the newest and most exciting developments   
   in systems that cover some aspects of the entire process of scientific   
   discovery (including, e.g, representation, exploration, conjecture   
   generation, validation, and publishing/reporting).  Of particular   
   interest is how the current technologies can fit together to form an   
   environment that augments human reasoner's vision and reach, and what   
   goals should be set in order to move closer to the complete   
   mechanization of general scientific discovery---or at least closer to   
   machines operating as intelligent assistants in the search for new   
   discoveries.   
      
      
   Topics of interest include, but are not limited to:   
      
   * Given progress on multiple fronts relevant to scientific discovery,   
   can *comprehensive* or *multi-faceted* discovery systems be developed?   
      
   * What role does/should knowledge, knowledge-based systems, and the   
   semantic web, play in the development of AI discovery systems?   
      
   * Systems for human-machine collaborative discovery, and educational   
   aids in discover and problem solving.   
      
   * Can architectures for carefully describing, in computational terms,   
   the overall process of scientific discovery be devised?   
      
   * What role can the cognitive science of discovery (creativity,   
   invention, etc.) play in AI's quest for discovery systems?   
      
      
   Submissions   
      
   We invite submissions for papers that introduce new research   
   developments in these and related areas.  Potential participants may   
   submit full papers (up to 8 pages in length) or short papers (1-2   
   pages in length) by May 20, 2008 sent electronically to   
   shilla@cs.rpi.edu. We are not actively seeking opinion papers, but   
   will consider all submissions.   
      
      
   Important Dates   
      
   Paper submission: May 20, 2008   
   Notification of acceptance: June 6, 2008   
   Camera ready papers: September 12, 2008   
      
      
   Organizing Committee   
      
   Andrew Shilliday (co-chair), Rensselaer Polytechnic Institute; Selmer   
   Bringsjord (co-chair), Rensselaer Polytechnic Institute; Alan Bundy,   
   University of Edinburgh; Simon Colton, Imperial College London; Doug   
   Lenat, Cycorp.   
      
      
   For additional information, pleas consult the supplementary symposium   
   web site at http://www.cogsci.rpi.edu/conferences/AAAI/FallSymposium2008/   
      
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