In the opening scene of the first Matrix movie, which debuted in 1999, an exchange occurs between a somber and mysterious government entity identified only as “Agent Smith,” played by Hugo Weaving, and a software programmer and part-time computer hacker named Anderson, played by Keanu Reeves.
In the exchange, the government agent reveals the extent of their surveillance of Anderson’s activities, saying, “As you can see, we’ve had our eye on you for some time, Mr. Anderson.” He then attempts to recruit Anderson to find the elusive Morpheus, played by Laurence Fishburne. Later in the movie we learn that Agent Smith is, in fact, a computer artifact or intelligent agent.
Today, Agent Smith has been re-imagined as a “good guy” in a General Electric commercial that advertises the intelligence of General Electric’s hospital management software.
Coincidentally, research on intelligent agents is at the forefront for College of Information Sciences and Technology Professors John Yen and Michael McNeese, who were recently awarded U. S. patent number US 8,442,839: Agent-based Collaborative Recognition-Primed Decision-Making.
In the patent application, the duo describes the concept of using a new collaborative intelligent agent framework, originally developed by Yen and his students, called CAST (Collaborative Agents for Simulating Teamwork), enhanced with a recognition-primed decision (RPD) model.
The RPD model is a cognitive model developed by Gary Klein to describe how people make rapid decisions when faced with complex situations. The resulting framework enables the development of software agents that use cognitive processes similar to that used by human experts (the RPD model) and interact with each other in a collaborative way similar to how humans interact in team-decision processes.
Yen and McNeese’s development is extraordinary for a number of reasons, not the least of which is that this is not simply a theoretical construct (although even that itself would be remarkable). Instead, they have applied this concept to developing intelligent agent teams that interact with human teams in real-world, decision-making environments such as crisis management, military situational awareness, and homeland security.
In effect, an interacting team of software agents, each having specialized knowledge and processing capability, interact with each other to analyze data, form hypotheses, evaluate alternatives, determine what types of information are needed for a dynamic decision-making environment, and support human analysts.
This virtual team of software agents interacts with and supports a real, distributed team of human agents (analysts) to solve complex problems. In this interactive environment, agents interact with agents, agents interact with humans, humans interact with humans and, in theory, no one “knows” who is human and who isn’t! The matrix is here and now – guided by IST researchers.
This work exemplifies the nature of IST: understanding how human cognition works, how humans interact with each other, the complexities of information analysis and decision-making, how to develop computationally effective automated reasoning (viz., artificial intelligence), and finally, how to evaluate the effectiveness of such techniques by experiments involving human subjects using a “living laboratory” approach.
This is what IST research is about – collaboration, understanding humans and human interaction as well as computers and computation, and applying it to real-world situations.
I congratulate John Yen and Mike McNeese on this exciting accomplishment and look forward to the future implications of this research, which are boundless. Imagine having your own “advisory team” to assist in everything from addressing complex problems to navigating new situations. You could have “guardian agents” to aid you when traveling in unknown countries or to help you in addressing health or financial issues. I could go on speculating, but I have to interrupt this blog – Agent Smith is seeking my attention!