As many of you already know, the design of the COSA software model was heavily influenced by my ongoing research in artificial intelligence. One of the problems that every serious AI researcher or robot brain designer must confront is conflict resolution. How does one keep a robot from doing stupid things like trying to open and close the door at the same time, or trying to put both feet in front of the other? In other words, how can a behaving system (which is what a COSA program is) control the selection of its actions without introducing logical contradictions or conflicts? GOFAI (good old fashioned AI) experts would immediately suggest the use of predicate calculus with which to manipulate various symbols. Aside from the fact that the symbol manipulation approach to doing AI has been a dismal failure, the brain is known to process discrete signals (unnamed events), not symbols.
The beauty of discrete signal processing is that the behavioral logic of a signal-based intelligent system is not symbolic in nature but temporal. Timing is everything. This simplifies learning tremendously because there can only be two temporal correlations between events: they are either concurrent or sequential. Of course, a COSA program does not have to learn temporal correlations but event timing is the key to resolving conflicts in the program’s behavior. Logical consistency in COSA is governed by a single powerful principle that I have been calling the principle of motor coordination (PMC). I am not going to expand on it here but suffice it to say that the use of the PMC will find and resolve all internal logical conflicts in the behavior of a COSA program regardless of its complexity. The power of the PMC is its simplicity.