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» Learning Behaviors Models for Robot Execution Control
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AIIDE
2009
13 years 9 months ago
Improving Offensive Performance Through Opponent Modeling
Although in theory opponent modeling can be useful in any adversarial domain, in practice it is both difficult to do accurately and to use effectively to improve game play. In thi...
Kennard Laviers, Gita Sukthankar, David W. Aha, Ma...
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 3 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
ESTIMEDIA
2006
Springer
14 years 10 days ago
Loop Nest Splitting for WCET-Optimization and Predictability Improvement
This paper presents the influence of the loop nest splitting source code optimization on the worst-case execution time (WCET). Loop nest splitting minimizes the number of executed...
Heiko Falk, Martin Schwarzer
ROBOCUP
2004
Springer
106views Robotics» more  ROBOCUP 2004»
14 years 2 months ago
Predicting Opponent Actions by Observation
In competitive domains, the knowledge about the opponent can give players a clear advantage. This idea lead us in the past to propose an approach to acquire models of opponents, ba...
Agapito Ledezma, Ricardo Aler, Araceli Sanch&iacut...
FUIN
2008
119views more  FUIN 2008»
13 years 8 months ago
Modeling Communication with Synchronized Environments
A deterministic behavior of systems composed of several modules is a desirable design goal. Assembling a complex system from components requires also a high degree of re-usability....
Tiberiu Seceleanu, Axel Jantsch