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ICML
2010
IEEE
13 years 6 months ago
Constructing States for Reinforcement Learning
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
M. M. Hassan Mahmud
ATAL
2007
Springer
14 years 2 months ago
Policy recognition for multi-player tactical scenarios
This paper addresses the problem of recognizing policies given logs of battle scenarios from multi-player games. The ability to identify individual and team policies from observat...
Gita Sukthankar, Katia P. Sycara
AIPS
2009
13 years 9 months ago
Automatic Derivation of Memoryless Policies and Finite-State Controllers Using Classical Planners
Finite-state and memoryless controllers are simple action selection mechanisms widely used in domains such as videogames and mobile robotics. Memoryless controllers stand for func...
Blai Bonet, Héctor Palacios, Hector Geffner
AI
2006
Springer
13 years 8 months ago
Robot introspection through learned hidden Markov models
In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behaviour...
Maria Fox, Malik Ghallab, Guillaume Infantes, Dere...
CHI
2005
ACM
14 years 8 months ago
Conversing with the user based on eye-gaze patterns
Motivated by and grounded in observations of eye-gaze patterns in human-human dialogue, this study explores using eye-gaze patterns in managing human-computer dialogue. We develop...
Pernilla Qvarfordt, Shumin Zhai