Design and prototype implementation of a communication mechanism for reward-maximizing AGI

Abstract

We designed and implemented a prototype mechanism for agents to communicate with each other for the purpose of reward maximization. The agents can be interpreted as solving POMDP in an approximate manner, and are designed to use their actions, inferences, and communication in a purposive manner. We examined the validity of the design by writing a test program that runs on the prototype implementation. This mechanism is also a candidate for a computational model of human communication.