Exploring Efficient Communication in Interactive Dynamic Influence Diagrams

Interactive Dynamic Influence Diagrams (I-DIDs) provide an efficient method for representing multiagent sequential decision problem. By extending I-DIDs with communication, agents are able to exchange their information to learn more about the world. Note that communication is not free, agents should decide whether to communicate or not. This computational process is very time consuming, so it won’t work well in a large problem. In this paper, we first study communication based on the framework of I-DIDs, then discuss when agents suppose to communicate considering the cost and the limit resource. Experiments show that our communication algorithm works efficiently in tiger problem. We conclude that communication not only can improve the total rewards, but picking the right time to communicate is also beneficial to agents.