881 citations · 1.4k across the 15 of their papers we have counts for
15 papers
Online Speedup Learning for Optimal Planning
Carmel Domshlak, Erez Karpas, Shaul Markovitch
Domain-independent planning is one of the foundational areas in the field of Artificial Intelligence. A description of a planning task consists of an initial world state, a goal, a…
Implicit Abstraction Heuristics
Michael Katz, Carmel Domshlak
State-space search with explicit abstraction heuristics is at the state of the art of cost-optimal planning. These heuristics are inherently limited, nonetheless, because the size…
Generic Preferences over Subsets of Structured Objects
Maxim Binshtok, Ronen I. Brafman, Carmel Domshlak +1
Various tasks in decision making and decision support systems require selecting a preferred subset of a given set of items. Here we focus on problems where the individual items are…
Monte-Carlo Planning: Theoretically Fast Convergence Meets Practical Efficiency
Zohar Feldman, Carmel Domshlak
Popular Monte-Carlo tree search (MCTS) algorithms for online planning, such as epsilon-greedy tree search and UCT, aim at rapidly identifying a reasonably good action, but provide…
Cost-Sharing in Bayesian Knowledge Bases
Solomon Eyal Shimony, Carmel Domshlak, Eugene Santos
Bayesian knowledge bases (BKBs) are a generalization of Bayes networks and weighted proof graphs (WAODAGs), that allow cycles in the causal graph. Reasoning in BKBs requires findin…
Introducing Variable Importance Tradeoffs into CP-Nets
Ronen I. Brafman, Carmel Domshlak
The ability to make decisions and to assess potential courses of action is a corner-stone of many AI applications, and usually this requires explicit information about the decision…