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PKDD
2010
Springer
122views Data Mining» more  PKDD 2010»
13 years 7 months ago
Exploration in Relational Worlds
Abstract. One of the key problems in model-based reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large relational domains, in wh...
Tobias Lang, Marc Toussaint, Kristian Kersting
ICTAI
2010
IEEE
13 years 7 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...
PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
13 years 7 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...
QEST
2010
IEEE
13 years 7 months ago
Reasoning about MDPs as Transformers of Probability Distributions
We consider Markov Decision Processes (MDPs) as transformers on probability distributions, where with respect to a scheduler that resolves nondeterminism, the MDP can be seen as ex...
Vijay Anand Korthikanti, Mahesh Viswanathan, Gul A...
ICCV
2009
IEEE
13 years 6 months ago
Efficient human pose estimation via parsing a tree structure based human model
Human pose estimation is the task of determining the states (location, orientation and scale) of each body part. It is important for many vision understanding applications, e.g. v...
Xiaoqin Zhang, Changcheng Li, Xiaofeng Tong, Weimi...