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17 years 4 months ago
Reinforcement Learning: An Introduction
"Reinforcement learning is learning what to do how to map situations to actions so as to maximize a numerical reward signal. The learner is not told which actions to take, as ...
Richard S. Sutton, Andrew G. Barto
PERCOM
2006
ACM
16 years 6 months ago
Pushing Doors for Modeling Contexts with OWL DL a Case Study
In this paper we present an integrated view for modeling and reasoning for context applications using OWL DL. In our case study, we describe a task driven approach to model typica...
Anni-Yasmin Turhan, Thomas Springer, Michael Berge...
CIG
2005
IEEE
16 years 3 days ago
Similarity-based Opponent Modelling using Imperfect Domain Theories
Abstract- This paper proposes a similarity-based approach for opponent modelling in multi-agent games. The classification accuracy is increased by adding derived attributes from i...
Timo Steffens
SYNASC
2005
IEEE
133views Algorithms» more  SYNASC 2005»
16 years 2 days ago
Emotional Ant Based Modeling of Crowd Dynamics
It is known that one of the most disastrous forms of collective human behavior is the kind of crowd stampede induced by panic. This situation often leads to fatalities as people a...
Soumya Banerjee, Crina Grosan, Ajith Abraham
DEXAW
2003
IEEE
101views Database» more  DEXAW 2003»
15 years 11 months ago
The Patia Autonomic Webserver: Feasibility Experimentation
This paper introduces the Patia Autonomic webserver, which has been designed to be self-monitoring and adaptive to not only improve webserver performance but robustness in terms o...
Julie A. McCann, Gawesh Jawaheer