Specific Challenges/Research Agenda Items

  • • Using all the knowledge gained within natural gas supply chains to discern what areas make sense for developing sociocognitive technologies and decision aids, and then thinking through what the necessary information architecture and requisite data/database is for a given prototype.
  • • Appropriating various cognitive decision aides and embedding them within a preexisting scaled-world environment can be difficult and time consuming.
  • • Figuring out the extent of function allocation between human and intelligent agents can be tricky and must evolve from other elements of the LLF.
  • • Determining when research saturation has occurred can be problematic given that LLF is cyclical and could potentially go on ad infinitum (i.e., at what point does the cycle end?).

Opportunities to Move Research Forward

  • • Evaluate the effectiveness of intelligent agents and other cognitive decision aiding techniques on the decision-making processes of novices versus those of experts.
  • • Compare various cognitive decision aides on knowledge acquisition and transfer among experts.
  • • For instance, do these aides support or inhibit experts given their already preexisting knowledge of a given context?
  • • Or, to what extent do these aides support or inhibit learning for novices?
  • • In addition, had given these aides, which group (i.e., expert or novice) benefits the most?
  • • Testing human-autonomous interaction within the realm of distributed and collocated teams is an area that should provide meaningful results for the natural gas supply chain.
 
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