Learning, Planning, and Acting with Models
Thanard Kurutach [2021]
Extracting and Using Preference Information from the State of the World
Rohin Shah [2020]
On Building Generalizable Learning Agents
Yi Wu [2019]
Principles of Metalevel Control
Nicholas Hay [2016]
Signal-based Bayesian Seismic Monitoring
David Moore [2016]
Efficient inference algorithms for near-deterministic systems
Shaunak Chatterjee [2013]
Model-based Bayesian Seismic Monitoring
Nimar S Arora [2012]
Hierarchical Methods for Optimal Long-Term Planning
Jason Wolfe [2011]
Nonparametric Hierarchical Bayesian Models of Categorization
Kevin Canini [2011]
Efficient Motor Control Learning
Gregory Donnell Lawrence [2009]
Probabilistic Models with Unknown Objects
Brian Christopher Milch [2006]
Exploiting Locality in Probabilistic Inference
Mark A. Paskin [2004]
Probabilistic Graphical Models and Algorithms for Genomic Analysis
Eric Poe Xing [2004]
Identity Uncertainty
Hanna M. Pasula [2003]
Programmable Reinforcement Learning Agents
David Andre [2003]
Value Determination with Function Approximation
Vassilis A. Papavassiliou [2003]
Dynamic Bayesian Networks: Representation, Inference and Learning
Kevin P. Murphy [2002]
Reinforcement Learning for Autonomous Vehicles
Jeffrey R. N. Forbes [2002]
Online Ensemble Learning
Nikunj C. Oza [2001]
Probabilistic Reasoning in Intelligent Vehicle Highway Systems
Timothy T.-M. Huang [1999]
Bayesian Problem-Solving Applied to Scheduling
Othar Hansson [1998]
Hierarchical Control and Learning for Markov Decision Processes
Ronald E. Parr [1998]
Speech Recognition with Dynamic Bayesian Networks
Geoffrey G. Zweig [1998]
Belief Network Induction
Charles Ronald Musick [1994]
Rational Search
Andrew E. Mayer [1994]
Operational Rationality through Compilation of Anytime Algorithms
Shlomo Zilberstein [1993]
RALPH-MEA: A Real-Time, Decision-Theoretic Agent Architecture
Gary Hayato Ogasawara [1993]
PAGODA: A Model for Autonomous Learning in Probabilistic Domains
Marie Ellen desJardins [1992]