Neural Computation with Rings of Quasiperiodic Oscillators

This approach will enab le robots to have complex responses to unfamiliar situations without the need for e ither a computationally intensive central processor or preprogrammed prior antic ipation of all possible situations. Conventional robots achieve adaptive behavi or by either digital programmed world-models (Bekey, 2005) or through large numbers of finite state machines programmed for small tasks - sensor input/actuator output (Arkin, 1999). The former approach requires massive amounts of up-front programming and re sults in a brittle computational system. New and/or unexpected events will result in r obot behavior not necessarily appropriate to the situation since the robot can only draw from a limited library of preprogrammed behaviors. The latter approach has the a dvantage of not requiri ng a world model but suffers from the same problem of not re sponding appropriately in many situations.