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GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 3 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
DIMVA
2007
15 years 1 months ago
Distributed Evasive Scan Techniques and Countermeasures
Scan detection and suppression methods are an important means for preventing the disclosure of network information to attackers. However, despite the importance of limiting the inf...
Min Gyung Kang, Juan Caballero, Dawn Xiaodong Song
NIPS
2007
15 years 1 months ago
A Game-Theoretic Approach to Apprenticeship Learning
We study the problem of an apprentice learning to behave in an environment with an unknown reward function by observing the behavior of an expert. We follow on the work of Abbeel ...
Umar Syed, Robert E. Schapire
ECIS
2004
15 years 1 months ago
SMEs and internet adoption strategy: who do SMEs listen to?
Governments have developed policies and strategies which are designed to assist SMEs to become eenabled. It is not clear what impact these strategies have on SMEs. There is some e...
Martin Beckinsale, Margi Levy
AIPS
2003
15 years 1 months ago
A Framework for Planning in Continuous-time Stochastic Domains
We propose a framework for policy generation in continuoustime stochastic domains with concurrent actions and events of uncertain duration. We make no assumptions regarding the co...
Håkan L. S. Younes, David J. Musliner, Reid ...