How to endow case-based reasoning systems with effective case adaptation capabilities is a classic problem. A significant impediment to developing automated adaptation procedures i...
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang...
We introduce a new bias for rule learning systems. The bias only allows a rule learner to create a rule that predicts class membership if each test of the rule in isolation is pred...
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
Modeling the behavior of imperfect agents from a small number of observations is a difficult, but important task. In the singleagent decision-theoretic setting, inverse optimal co...