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» Reinforcement Learning: An Introduction
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ALIFE
2002
13 years 8 months ago
Ant Colony Optimization and Stochastic Gradient Descent
In this paper, we study the relationship between the two techniques known as ant colony optimization (aco) and stochastic gradient descent. More precisely, we show that some empir...
Nicolas Meuleau, Marco Dorigo
AROBOTS
2008
131views more  AROBOTS 2008»
13 years 8 months ago
Active audition using the parameter-less self-organising map
This paper presents a novel method for enabling a robot to determine the position of a sound source in three dimensions using just two microphones and interaction with its environm...
Erik Berglund, Joaquin Sitte, Gordon Wyeth
AGI
2011
12 years 12 months ago
Measuring Agent Intelligence via Hierarchies of Environments
Under Legg’s and Hutter’s formal measure [1], performance in easy environments counts more toward an agent’s intelligence than does performance in difficult environments. An ...
Bill Hibbard
CORR
2006
Springer
140views Education» more  CORR 2006»
13 years 8 months ago
Nearly optimal exploration-exploitation decision thresholds
While in general trading off exploration and exploitation in reinforcement learning is hard, under some formulations relatively simple solutions exist. Optimal decision thresholds ...
Christos Dimitrakakis
ICSE
2007
IEEE-ACM
14 years 2 months ago
ACL2s: "The ACL2 Sedan"
ACL2 is the latest inception of the Boyer-Moore theorem prover, the 2005 recipient of the ACM Software System Award. In the hands of an expert, it feels like a finely tuned race ...
Peter C. Dillinger, Panagiotis Manolios, Daron Vro...