We propose a novel method for constructing utility models by learning from observed negotiation actions. In particular, we show how offers and counter-offers in negotiation can be...
We study leading-edge local search heuristics for balanced hypergraph partitioning and Boolean satisfiability, intending the generalization of such heuristics beyond their origina...
Multi-level spatial aggregates are important for data mining in a variety of scientific and engineering applications, from analysis of weather data (aggregating temperature and p...
Information personalization is fertile ground for application of AI techniques. In this article I relate personalization to the ability to capture partial information in an informa...
In multiagent environments, forms of social learning such as teaching and imitation have been shown to aid the transfer of knowledge from experts to learners in reinforcement lear...
Most probabilistic inference algorithms are specified and processed on a propositional level. In the last decade, many proposals for algorithms accepting first-order specificat...
This paper introduces the Point-Based Value Iteration (PBVI) algorithm for POMDP planning. PBVI approximates an exact value iteration solution by selecting a small set of represen...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...