BACKGROUND OF THE INVENTION

Embodiments of the invention relate to systems of autonomous distributed agents that perform predetermined tasks.

Conventionally, systems of autonomous distributed agents may perform predetermined tasks through reinforcement learning. However, such systems lack efficiency as a result of errors in communication between the agents, and as a result of errors associated with the detectors of the agents.

There exists a need for a system and method for controlling autonomous agents to perform a predetermined task using reinforcement learning, which takes into account errors in communication and detection.

SUMMARY OF THE INVENTION

Aspects of the present disclosure provides a system and method for controlling autonomous agents to perform a predetermined task using reinforcement learning, which takes into account errors in communication and detection.

An aspect of the present disclosure is drawn to a system for performing a predetermined function within a total area of operation, wherein system includes a first autonomous agent, a second autonomous agent, and a third autonomous agent. The first autonomous agent includes a first agent detector, a first agent communication component and a first agent controller. The first agent detector is operable to detect a first agent parameter within a first agent area and to generate a first agent parameter signal based on the detected first agent parameter. The first agent controller is operable to instruct the first autonomous agent to perform an initial first agent task and to perform a subsequent first agent task. The second autonomous agent includes a second agent detector, a second agent communication component and a second agent controller. The second agent detector is operable to detect a second agent parameter within a second agent area and to generate a second agent parameter signal based on the detected second agent parameter. The second agent communication component is operable to transmit the second agent parameter signal to the first agent communication component. The second agent controller is operable to instruct the second autonomous agent to perform an initial second agent task and to perform a subsequent second agent task. The third autonomous agent includes a third agent detector, a third agent communication component and a third agent controller. The third agent detector is operable to detect a third agent parameter within a third agent area and to generate a third agent parameter signal based on the detected third agent parameter. The third agent communication component is operable to transmit the third agent parameter signal to the first agent communication component and to the second agent communication component. The third agent controller is operable to instruct the third autonomous agent to perform an initial third agent task and to perform a subsequent third agent task. The first agent communication component is operable to transmit the first agent parameter signal to the second agent communication component and to the third agent communication component. The second agent communication component is further operable to transmit the second agent parameter signal to the third agent communication component. The first agent controller is operable to instruct the first autonomous agent to perform the subsequent first agent task based on the first agent parameter signal, the second agent parameter signal, the third agent parameter signal and a predetermined reward function using reinforcement learning and a first Kalman consensus filter. The second agent controller is operable to instruct the second autonomous agent to perform the subsequent second agent task based on the first agent parameter signal, the second agent parameter signal, the third agent parameter signal and the predetermined reward function using reinforcement learning and as second Kalman consensus filter. The third agent controller is operable to instruct the third autonomous agent to perform the subsequent third agent task based on the first agent parameter signal, the second agent parameter signal, the third agent parameter signal and the predetermined reward function using reinforcement learning and a third Kalman consensus filter. The first agent area is less than and within the total area of operation. The second agent area is less than and within the total area of operation.

