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» Learning action effects in partially observable domains
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ACL
2009
14 years 7 months ago
Reinforcement Learning for Mapping Instructions to Actions
In this paper, we present a reinforcement learning approach for mapping natural language instructions to sequences of executable actions. We assume access to a reward function tha...
S. R. K. Branavan, Harr Chen, Luke S. Zettlemoyer,...
AIED
2005
Springer
15 years 3 months ago
The Effect of Explaining on Learning: a Case Study with a Data Normalization Tutor
: Several studies have shown that explaining actions increases students’ knowledge. In this paper, we discuss how NORMIT supports self-explanation. NORMIT is a constraint-based t...
Antonija Mitrovic
UAI
1994
14 years 11 months ago
A Probabilistic Calculus of Actions
Wepresenta symbolicmachinerythatadmits bothprobabilisticand causalinformation abouta givendomainand producesprobabilisticstatementsabouttheeffectofactions andtheimpactof observati...
Judea Pearl
ATAL
2004
Springer
15 years 3 months ago
Interactive POMDPs: Properties and Preliminary Results
This paper presents properties and results of a new framework for sequential decision-making in multiagent settings called interactive partially observable Markov decision process...
Piotr J. Gmytrasiewicz, Prashant Doshi
NIPS
2004
14 years 11 months ago
Resolving Perceptual Aliasing In The Presence Of Noisy Sensors
Agents learning to act in a partially observable domain may need to overcome the problem of perceptual aliasing
Guy Shani, Ronen I. Brafman