Collaborative medical diagnosis through Fuzzy Petri Net based agent argumentation

Online health information services and self diagnosis systems become popular recent years. We propose a computing model for collaborative medical diagnosis through multi agent argumentation. In this model, the agents are able to communicate with each other to share information, critique and verify each other's knowledge, and collaboratively make diagnosis based on multiple agents' knowledge through an argumentation process. Fuzzy Petri Net (FPN) is adopted as the agents' knowledge model. Different from the commonly used FPNs that assign tokens in places, we assign tokens on arcs and also give places capability in controlling the inference of FPN. The FPN based argumentation is automated with algorithms. The proposed model can be employed to achieve collaborative healthcare diagnosis systems, where agents with different expertise collaboratively argue with each other to come up with a mutually agreed diagnosis.