Multi-Agent Filtering with Infinitely Nested Beliefs (2009)
Luke S. Zettlemoyer, Brian Milch, Leslie Pack Kaelbling
In partially observable worlds with many agents, nested beliefs are formed when agents simultaneously reason about the unknown state of the world and the beliefs of the other agents. The multi-agent...
Kristian Kersting, Brian Milch, Luke S. Zettlemoyer, Michael Haimes, Leslie Pack Kaelbling
do not scale well to large populations • Lifted inference idea: • Many individuals are interchangeable in model • Exploit that symmetry to speed up inference
Reasoning about Large Populations with Lifted Probabilistic Inference (2008)
Kristian Kersting, Brian Milch, Luke S. Zettlemoyer, Michael Haimes, Leslie Pack Kaelbling
We use a concrete problem in the context of planning meetings to show how lifted probabilistic inference can dramatically speed up reasoning. We also extend lifted inference to deal with cardinality...
Kaelbling. Learning symbolic models of stochastic domains (2008)
Hanna M. Pasula, Luke S. Zettlemoyer, Leslie Pack Kaelbling
In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a probabilistic, relational planning rule representation that compactly models...
Kaelbling. Learning symbolic models of stochastic domains (2008)
Hanna M. Pasula, Luke S. Zettlemoyer, Leslie Pack Kaelbling
In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a probabilistic, relational planning rule representation that compactly models...
Kaelbling. Learning symbolic models of stochastic domains (2008)
Hanna M. Pasula, Luke S. Zettlemoyer, Leslie Pack Kaelbling
In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a a new probabilistic planning rule representation to compactly model model noisy,...
Learning Probabilistic Relational Dynamics for Multiple Tasks (2008)
Deshpande, Ashwin, Milch, Brian, Zettlemoyer, Luke S., Kaelbling, Leslie Pack
The ways in which an agent's actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This extended abstract addresses the problem of learning...
Logical Particle Filtering (2008)
Zettlemoyer, Luke S., Pasula, Hanna M., Pack Kaelbling, Leslie
In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical particle filtering algorithm....
Logical particle filtering (2007)
Luke S. Zettlemoyer, Hanna M. Pasula, Leslie Pack Kaelbling
Abstract. In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical particle filtering...
Online learning of relaxed CCG grammars for parsing to logical form (2007)
Luke S. Zettlemoyer, Michael Collins
We consider the problem of learning to parse sentences to lambda-calculus representations of their underlying semantics and present an algorithm that learns a weighted combinatory categorial grammar...
Online learning of relaxed CCG grammars for parsing to logical form (2007)
Luke S. Zettlemoyer, Michael Collins
We consider the problem of learning to parse sentences to lambda-calculus representations of their underlying semantics and present an algorithm that learns a weighted combinatory categorial grammar...
Learning planning rules in noisy stochastic worlds (2005)
We present an algorithm for learning a model of the effects of actions in noisy stochastic worlds. We consider learning in a 3D simulated blocks world with realistic physics. To model this world, we...
The User Interface as an Agent Environment (2000)
Robert St. Amant, Luke S. Zettlemoyer
Theoretically motivated planning systems often make assumptions about their environments, in areas such as the predictability of action effects, static behavior of the environment, and access to...
A Visual Medium for Programmatic Control of Interactive Applications (1999)
Luke S. Zettlemoyer, Robert St. Amant
The VisMap system provides for "visual manipulation" of arbitrary off-the-shelf applications, through an application's graphical user interface. VisMap's API-independent control...
Towards Narrative-Centered Learning Environments (1999)
Bradford W. Mott, Charles B. Callaway, Luke S. Zettlemoyer, Seung Y. Lee, James C. Lester, Muriel Rukeyser
Because narrative plays such a central role in cognition and culture, narrative-centered curricula have been the subject of increasing attention. By taking advantage of the inherent structure of...
Explanatory Lifelike Avatars: Performing User Centered Tasks (1999)
James C. Lester, Luke S. Zettlemoyer, Joël P. Grégoire, William H. Bares
Because of their multimodal communicative abilities and strong visual presence, animated pedagogical agents offer significant promise for 3D learning environments. We describe a new class of animated...
Habitable 3D learning environments for situated learning (1998)
William H. Bares, Luke S. Zettlemoyer, James C. Lester
Abstract. The growing emphasis on learner-centered education focuses on intrinsically motivated learning via engaging problem-solving activities. Habitable 3D learning environments, in which learners...
Task-sensitive cinematography interfaces for interactive 3d learning environments (1998)
William H. Bares, Luke S. Zettlemoyer, Dennis W. Rodriguez, James C. Lester
Interactive 3D learning environments can provide rich problemsolving experiences with unparalleled visual impact. In these environments, students interactively solve problems by directing their...