An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Deploying a classifier to large-scale systems such as the web requires careful feature design and performance evaluation. Evaluation is particularly challenging because these larg...
We present the design and evaluation of an on-thefly data-race-detection technique that handles applications written for the lazy release consistent (LRC) shared memory model. We ...
We design algorithms for computing approximately revenue-maximizing sequential postedpricing mechanisms (SPM) in K-unit auctions, in a standard Bayesian model. A seller has K copi...