19 citations · 123 across the 25 of their papers we have counts for
3 papers · 1 filter
Explainable Models via Compression of Tree Ensembles
Siwen Yan, Sriraam Natarajan, Saket Joshi +2
Ensemble models (bagging and gradient-boosting) of relational decision trees have proved to be one of the most effective learning methods in the area of probabilistic logic models…
Parametrically Retargetable Decision-Makers Tend To Seek Power
Alexander Matt Turner, Prasad Tadepalli
If capable AI agents are generally incentivized to seek power in service of the objectives we specify for them, then these systems will pose enormous risks, in addition to enormous…
Formalizing the Problem of Side Effect Regularization
Alexander Matt Turner, Aseem Saxena, Prasad Tadepalli
AI objectives are often hard to specify properly. Some approaches tackle this problem by regularizing the AI's side effects: Agents must weigh off "how much of a mess they make" wi…