117 citations · 349 across the 7 of their papers we have counts for
7 papers
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Jia-Hong Wu, Robert Givan
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provided,…
Model Reduction Techniques for Computing Approximately Optimal Solutions for Markov Decision Processes
Thomas L. Dean, Robert Givan, Sonia Leach
We present a method for solving implicit (factored) Markov decision processes (MDPs) with very large state spaces. We introduce a property of state space partitions which we call e…
Inductive Policy Selection for First-Order MDPs
Sung Wook Yoon, Alan Fern, Robert Givan
We select policies for large Markov Decision Processes (MDPs) with compact first-order representations. We find policies that generalize well as the number of objects in the domain…
Estimating Densities with Non-Parametric Exponential Families
Lin Yuan, Sergey Kirshner, Robert Givan
We propose a novel approach for density estimation with exponential families for the case when the true density may not fall within the chosen family. Our approach augments the suf…
Approximate Policy Iteration with a Policy Language Bias: Solving Relational Markov Decision Processes
A. Fern, R. Givan, S. Yoon
We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual…
Specific-to-General Learning for Temporal Events with Application to Learning Event Definitions from Video
A. Fern, R. Givan, J. M. Siskind
We develop, analyze, and evaluate a novel, supervised, specific-to-general learner for a simple temporal logic and use the resulting algorithm to learn visual event definitions fro…