REM: Reflective Evolutionary Mind


REM is an operating environment for intelligent agents. The focus of the REM project is on reflective evolution. Agents in REM use reasoning about their own processing (i.e., reflection) to make adjustments to this processing (i.e., evolution). REM is a product of the Design & Intelligence Laboratory research group in the College of Computing at Georgia Tech. Participants in the REM project include Ashok K. Goel and J. William Murdock. Research on REM involves topics in Artificial Intelligence and Cognitive Science.


Human beings are tremendously effective at adapting to novel, unexpected situations. Compare a human accountant to an accounting program on a computer. The accounting program may be able to perform millions of computations per second, vastly more than the human can. However, even a very minor change to the format or organization of the information that an accounting program receives will typically render it unable to do anything at all. For example, if a typical accounting system is designed to accept a set of numbers (such as employee pay rates and hours worked) separated by commas and it receives this information separated by spaces, it will simply fail. In contrast, a human accountant would have no problem dealing with such a change. We hypothesize that this human ability is derived, at least in part, from the human's comprehension of his or her own reasoning.

A human working on some process understands the goal of the process, the techniques used to accomplish the goal, and the nature of the information that is used to support those techniques. In this example, the accountant knows that the numbers are inserted into the equations for computing wages and that the commas were present merely to separate the numbers. This information is also present implicitly in the accounting program (since it is able to perform these computations). However, the information is not represented in a way that the program can manipulate and alter. Furthermore, the program has no procedures for performing such alterations. Thus, unlike the human, the program is not able to infer that the spaces in the new records serve the same purpose as the commas in the old records and that the numbers in the new records should simply be used in the same way that the numbers in the old records were. The REM operating environment supports agents which are able to make modifications of this sort to themselves. Agents encoded in REM contain a model of how they work and can use this model to adapt to novel situations.


The following documents provides a comprehensive overview of the theoretical agenda behind the REM project: The following papers provides detailed information about individual aspects of the REM project: Finally, these aditional papers do not focus on REM, per se, but do provide some relevant additional background: