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ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
14 years 2 months ago
A formal framework for robot learning and control under model uncertainty
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
Robin Jaulmes, Joelle Pineau, Doina Precup
IROS
2009
IEEE
206views Robotics» more  IROS 2009»
14 years 2 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...
ICCS
2007
Springer
14 years 2 months ago
Adaptive Observation Strategies for Forecast Error Minimization
Abstract. Using a scenario of multiple mobile observing platforms (UAVs) measuring weather variables in distributed regions of the Pacific, we are developing algorithms that will ...
Nicholas Roy, Han-Lim Choi, Daniel Gombos, James H...
CORR
2011
Springer
230views Education» more  CORR 2011»
13 years 2 months ago
Computational Rationalization: The Inverse Equilibrium Problem
Modeling the behavior of imperfect agents from a small number of observations is a difficult, but important task. In the singleagent decision-theoretic setting, inverse optimal co...
Kevin Waugh, Brian Ziebart, J. Andrew Bagnell
IADIS
2004
13 years 9 months ago
Modelling Inductive Reasoning Ability for Adaptive Virtual Learning Environment
Inductive reasoning is one of the important characteristics of human intelligence. Researchers have regarded inductive reasoning as one of the seven primary mental abilities that ...
Taiyu Lin, Kinshuk, Paul McNab