On the Computation of Distributed Knowledge as the Greatest Lower Bound of Knowledge
share
Let L be a finite lattice and ℰ(L) be the set of join endomorphisms of L. We consider the problem of given L and f,g ∈ℰ(L), finding the greatest lower bound f ⊓_ℰ(L) g in the lattice ℰ(L). (1) We show that if L is distributive, the problem can be solved in time O(n) where n=| L |. The previous upper bound was O(n^2). (2) We provide new algorithms for arbitrary lattices and give experimental evidence that they are significantly faster than the existing algorithm. (3) We characterize the standard notion of distributed knowledge of a group as the greatest lower bound of the join-endomorphisms representing the knowledge of each member of the group. (4) We show that deciding whether an agent has the distributed knowledge of two other agents can be computed in time O(n^2) where n is the size of the underlying set of states. (5) For the special case of S5 knowledge, we show that it can be decided in time O(nα_n) where α_n is the inverse of the Ackermann function.
READ FULL TEXT
