An adaptive agent including an artificial neural network having a plurality of input nodes for receiving input signals and a plurality of output nodes generating responses. A situation value unit receives a plurality of the responses and generating a situation value signal. A change sensor coupled to receive the situation value signal generates an output signal representing a change of the situation value signal from a prior time to a current time. A connection coupling the change sensor output to one of the input nodes of the artificial neural network.
RELATED PATENT APPLICATIONS
The present invention claims the benefit of the filing date of U.S. Provisional Application No. 60/039,347 filed on Mar. 18, 1997 and is related to U.S. Pat. No. 5,802,506 issued on Sep. 1, 1998 both of which are invented by the inventor of the instant application and are incorporated herein by reference.
An autonomous adaptive agent which can learn verbal as well as nonverbal behavior. The primary object of the system is to optimize a primary value function over time through continuously learning how to behave in an environment (which may be physical or electronic). Inputs may include verbal advice or information from sources of varying reliability as well as direct or preprocessed environmental inputs. Desired agent behavior may include motor actions and verbal behavior which may constitute a system output (and which may also function "internally" to guide external actions. A further aspect involves an efficient "training" process by which the agent can be taught to utilize verbal advice and information along with environmental inputs.
