iLSTD: Eligibility Traces and Convergence Analysis

In this paper, we generalize the previous iLSTD algorithm and present three new results: (1)the first convergence proof for an iLSTD algorithm; (2) an extension to incorporate eligibility traces without changing the asymptotic computational complexity; and(3) the first empirical results with an iLSTD algorithm for a problem (mountain car) with feature vectors large enough (n 10, 000) to show substantial computationaladvantages over LSTD.