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ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
15 years 4 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
UAI
2004
14 years 11 months ago
Solving Factored MDPs with Continuous and Discrete Variables
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
AUTOMATICA
2007
124views more  AUTOMATICA 2007»
14 years 10 months ago
Motion planning in uncertain environments with vision-like sensors
In this work we present a methodology for intelligent path planning in an uncertain environment using vision like sensors, i.e., sensors that allow the sensing of the environment ...
Suman Chakravorty, John L. Junkins
JOI
2007
60views more  JOI 2007»
14 years 10 months ago
On the h-index, the size of the Hirsch core and Jin's A-index
Hirsch’s h-index seeks to give a single number that in some sense summarizes an author’s research output and its impact. Essentially, the h-index seeks to identify the most pr...
Quentin L. Burrell
BC
2002
84views more  BC 2002»
14 years 10 months ago
Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates
Synaptic plasticity is believed to underlie the formation of appropriate patterns of connectivity that stabilize stimulus-selective reverberations in the cortex. Here we present a ...
Stefano Fusi