Even if CYC is successful, it may prove hard for people to trust an agent instructed by someone else. Both the limited agents now distributed commercially and the artificial-intelligence versions under development rely on programming in one form or another. A third and possibly most promising approach employs techniques developed in the relatively young field of artificial life, whose practitioners study mechanisms by which organisms organize themselves and adapt in response to their environment. Their software is designed to change its behavior based on experience and on interactions with other agents. At the Massachusetts Institute of Technology, we have built software agents that continuously watch a person's actions and automate any regular patterns they detect.
Agents can also learn from agents that perform the same task.
Such collaboration can make it possible for collections of agents to act in sophisticated, apparently intelligent ways even though any single agent is quite simple. My colleagues and I have built such a system to develop agents to search a database and retrieve articles that might interest their users. Each succeeding generation matches its owner's interests better. In time, this approach could result in a complete electronic ecosystem housed in the next century's computer networks. Over time, these digital life-forms will fill different ecological niches some agents could evolve to be good indexers of databases, whereas others would use their indices to find articles of interest to a particular user.