Those of us engaged in artificial intelligence research have the historically unique privilege of asking and answering the most profound scientific and engineering questions that people have ever set for themselves--questions about the nature of those processes that separate us humans from the rest of the universe--namely intelligence, reason, perception, self-awareness, and language. It is clear--to most of us in AI, at least--that our field, perhaps together with molecular genetics, will be society's predominant scientific endeavor for the rest of this century and well into the next...

A formalism is presented for computing and organizing actions for autonomous agents in dynamic environments. We introduce the notion of teleo-reactive (T-R) programs whose execution entails the construction of circuitry for the continuous computation of the parameters and conditions on which agent action is based. In addition to continuous feedback, T-R programs support parameter binding and recursion. A primary difference between T-R programs and many other circuit-based systems is that the circuitry of T-R programs is more compact; it is constructed at run time and thus does not have to anticipate all the contingencies that might arise over all possible runs. In addition, T-R programs are intuitive and easy to write and are written in a form that is compatible with automatic planning and learning methods. We briefly describe some experimental applications of T-R programs in the control of simulated and actual mobile robots.