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» Learning Partially Observable Deterministic Action Models
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AMAI
2004
Springer
14 years 1 months ago
A Framework for Sequential Planning in Multi-Agent Settings
This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...
Piotr J. Gmytrasiewicz, Prashant Doshi
ACMICEC
2007
ACM
154views ECommerce» more  ACMICEC 2007»
13 years 11 months ago
Learning and adaptivity in interactive recommender systems
Recommender systems are intelligent E-commerce applications that assist users in a decision-making process by offering personalized product recommendations during an interaction s...
Tariq Mahmood, Francesco Ricci
ACL
2011
12 years 11 months ago
Semi-supervised latent variable models for sentence-level sentiment analysis
We derive two variants of a semi-supervised model for fine-grained sentiment analysis. Both models leverage abundant natural supervision in the form of review ratings, as well as...
Oscar Täckström, Ryan T. McDonald
ICRA
2008
IEEE
128views Robotics» more  ICRA 2008»
14 years 2 months ago
A point-based POMDP planner for target tracking
— Target tracking has two variants that are often studied independently with different approaches: target searching requires a robot to find a target initially not visible, and ...
David Hsu, Wee Sun Lee, Nan Rong
IUI
2004
ACM
14 years 1 months ago
Choosing when to interact with learners
In this paper, we describe a method for pedagogical agents to choose when to interact with learners in interactive learning environments. This method is based on observations of h...
Lei Qu, Ning Wang, W. Lewis Johnson