Integrating uncertainty handling formalisms in distributed artificial intelligence
Simon Parsons, Alessandro Saffiotti · 1993
. In distributed artificial intelligence systems it is important that the constituent intelligent systems communicate. This may be a problem if the systems use different methods to represent uncertain information. This paper presents a method that enables systems that use different uncertainty handling formalisms to qualitatively integrate their uncertain information, and argues that this makes it possible for distributed intelligent systems to achieve tasks that would otherwise be beyond them. 1 Introduction Distributed artificial intelligence (DAI) is that part of the field of artificial intelligence that deals with problem solving distributed amongst a number of intelligent systems. Thus DAI combines the power of artificial intelligence techniques with the advantages of distributed systems such as robustness and the ability to combine existing systems together in new configurations. One particular advantage of distributed artificial intelligence is the ability to take several exist...