Journal of Logic, Language and Information

, Volume 10, Issue 2, pp 183-209

First online:

Belief Fusion: Aggregating Pedigreed Belief States

  • Pedrito Maynard-ReidIIAffiliated withComputer Science Department, Stanford University
  • , Yoav ShohamAffiliated withComputer Science Department, Stanford University

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access


We introduce a new operator – belief fusion– which aggregates the beliefs of two agents, each informed by a subset of sources ranked by reliability. In the process we definepedigreed belief states, which enrich standard belief states with the source of each piece of information. We note that the fusion operator satisfies the invariants of idempotence, associativity, and commutativity. As a result, it can be iterated without difficulty. We also define belief diffusion; whereas fusion generally produces a belief state with more information than is possessed by either of its two arguments, diffusion produces a state with less information. Fusion and diffusion are symmetric operators, and together define a distributive lattice. Finally, we show that AGM revision can be viewed as fusion between a novice and an expert.

belief aggregation knowledge representation multi-agent systems