most citedDecision-Theoretic Planning: Structural Assumptions and Computational Leverage

1.1k citations · 2.3k across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2011881 cited

CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements

C. Boutilier, R. I. Brafman, C. Domshlak +2

Information about user preferences plays a key role in automated decision making. In many domains it is desirable to assess such preferences in a qualitative rather than quantitati…

cs.GT2011

Eliciting Forecasts from Self-interested Experts: Scoring Rules for Decision Makers

Craig Boutilier

Scoring rules for eliciting expert predictions of random variables are usually developed assuming that experts derive utility only from the quality of their predictions (e.g., scor…

cs.LG2011177 cited

Accelerating Reinforcement Learning through Implicit Imitation

C. Boutilier, B. Price

Imitation can be viewed as a means of enhancing learning in multiagent environments. It augments an agent's ability to learn useful behaviors by making intelligent use of the knowl…

cs.AI2011116 cited

Partial-Order Planning with Concurrent Interacting Actions

C. Boutilier, R. I. Brafman

In order to generate plans for agents with multiple actuators, agent teams, or distributed controllers, we must be able to represent and plan using concurrent actions with interact…

cs.AI20111.1k cited

Decision-Theoretic Planning: Structural Assumptions and Computational Leverage

C. Boutilier, T. Dean, S. Hanks

Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI p…