A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
In this paper, we applied online neuroevolution to evolve nonplayer characters for The Open Racing Car Simulator (TORCS). While previous approaches allowed online learning with per...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
This paper proposes a two-phase example-based machine translation methodology which develops translation templates from examples and then translates using template matching. This ...
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...