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AIED
2011
Springer
14 years 1 months ago
Faster Teaching by POMDP Planning
Both human and automated tutors must infer what a student knows and plan future actions to maximize learning. Though substantial research has been done on tracking and modeling stu...
Anna N. Rafferty, Emma Brunskill, Thomas L. Griffi...
83
Voted
JAIR
2006
122views more  JAIR 2006»
14 years 9 months ago
Solving Factored MDPs with Hybrid State and Action Variables
Efficient representations and solutions for large decision problems with continuous and discrete variables are among the most important challenges faced by the designers of automa...
Branislav Kveton, Milos Hauskrecht, Carlos Guestri...
AIPS
2007
14 years 12 months ago
Learning to Plan Using Harmonic Analysis of Diffusion Models
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
ATAL
2006
Springer
15 years 1 months ago
Winning back the CUP for distributed POMDPs: planning over continuous belief spaces
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
Pradeep Varakantham, Ranjit Nair, Milind Tambe, Ma...
JAIR
2008
107views more  JAIR 2008»
14 years 9 months ago
Planning with Durative Actions in Stochastic Domains
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
Mausam, Daniel S. Weld