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PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
13 years 8 months ago
Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
ICTAI
2010
IEEE
13 years 8 months ago
A Closer Look at MOMDPs
Abstract--The difficulties encountered in sequential decisionmaking problems under uncertainty are often linked to the large size of the state space. Exploiting the structure of th...
Mauricio Araya-López, Vincent Thomas, Olivi...
EMNLP
2010
13 years 8 months ago
Joint Training and Decoding Using Virtual Nodes for Cascaded Segmentation and Tagging Tasks
Many sequence labeling tasks in NLP require solving a cascade of segmentation and tagging subtasks, such as Chinese POS tagging, named entity recognition, and so on. Traditional p...
Xian Qian, Qi Zhang, Yaqian Zhou, Xuanjing Huang, ...
ISOLA
2010
Springer
13 years 9 months ago
Ten Years of Performance Evaluation for Concurrent Systems Using CADP
This article comprehensively surveys the work accomplished during the past decade on an approach to analyze concurrent systems qualitatively and quantitatively, by combining functi...
Nicolas Coste, Hubert Garavel, Holger Hermanns, Fr...
ICRA
2010
IEEE
143views Robotics» more  ICRA 2010»
13 years 9 months ago
Apprenticeship learning via soft local homomorphisms
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
Abdeslam Boularias, Brahim Chaib-draa
ICFEM
2010
Springer
13 years 9 months ago
Making the Right Cut in Model Checking Data-Intensive Timed Systems
Abstract. The success of industrial-scale model checkers such as Uppaal [3] or NuSMV [12] relies on the efficiency of their respective symbolic state space representations. While d...
Rüdiger Ehlers, Michael Gerke 0002, Hans-J&ou...
SIAMCO
2002
78views more  SIAMCO 2002»
13 years 10 months ago
Strong Optimality for a Bang-Bang Trajectory
In this paper we give sufficient conditions for a bang-bang regular extremal to be a strong local optimum for a control problem in the Mayer form; strong means that we consider the...
Andrei A. Agrachev, Gianna Stefani, PierLuigi Zezz...
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 10 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
INFORMS
1998
142views more  INFORMS 1998»
13 years 10 months ago
Distributed State Space Generation of Discrete-State Stochastic Models
High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models often requires the generatio...
Gianfranco Ciardo, Joshua Gluckman, David M. Nicol
INFORMATICALT
2000
85views more  INFORMATICALT 2000»
13 years 10 months ago
Sensitivity Analysis of Multivariable Systems in State Space
This paper contains measures to describe the matrix impulse response sensitivity of state space multivariable systems with respect to parameter perturbations.The parameter sensitiv...
Kazys Kazlauskas