Vertex-Reinforced Random Walk

Abstract

This paper considers a class of non-Markovian discrete-time random processes on a finite state space {1,...,d}. The transition probabilities at each time are influenced by the number of times each state has been visited and by a fixed a priori likelihood matrix, R, which is real, symmetric and nonnegative. Let S_i(n) keep track of the number of visits to state i up to time n, and form the fractional occupation vector, V(n), where v_i(n)=S_i(n)/(sum_{j=1}^d S_j(n)). It is shown that V(n) converges to a set of critical points for the quadratic form H with matrix R, and that under nondegeneracy conditions on R, there is a finite set of points such that with probability one, V(n)->p for some p in the set. There may be more than one p in this set for which P(V(n)->p)>0. On the other hand P(V(n)->p)=0 whenever p fails in a strong enough sense to be maximum for H.