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107
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GECCO
2006
Springer
15 years 4 months ago
2006
Springer
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
91
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ATAL
2009
Springer
15 years 7 months ago
2009
Springer
Certain observable features (tags), shared by a group of similar agents, can be used to signal intentions and can be effectively used to infer unobservable properties. Such infere...
163
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ATAL
2008
Springer
15 years 2 months ago
2008
Springer
We introduce eCAT, a tool that supports deriving test cases semi-automatically from goal-based analysis diagrams, generates meaningful test inputs based on agent interaction ontol...
86
Voted
ATAL
2009
Springer
15 years 7 months ago
2009
Springer
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...
100
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IDEAL
2005
Springer
15 years 6 months ago
2005
Springer
Artificial neural networks play an important role for pattern recognition tasks. However, due to poor comprehensibility of the learned network, and the inability to represent expl...