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GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
14 years 1 days ago
A Genetic Algorithm for Automatically Designing Modular Reinforcement Learning Agents
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
Isao Ono, Tetsuo Nijo, Norihiko Ono
AVI
2008
13 years 10 months ago
Exploring the role of individual differences in information visualization
In this paper, we describe a user study aimed at evaluating the effectiveness of two different data visualization techniques developed for describing complex environmental changes...
Cristina Conati, Heather Maclaren
TPDS
2002
126views more  TPDS 2002»
13 years 8 months ago
P-3PC: A Point-to-Point Communication Model for Automatic and Optimal Decomposition of Regular Domain Problems
One of the most fundamental problems automatic parallelization tools are confronted with is to find an optimal domain decomposition for a given application. For regular domain prob...
Frank J. Seinstra, Dennis Koelma
SIGIR
2003
ACM
14 years 1 months ago
Collaborative filtering via gaussian probabilistic latent semantic analysis
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Thomas Hofmann
AGENTS
2001
Springer
14 years 28 days ago
It knows what you're going to do: adding anticipation to a Quakebot
The complexity of AI characters in computer games is continually improving; however they still fall short of human players. In this paper we describe an AI bot for the game Quake ...
John E. Laird