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The ability to generalize is an important feature of any intelligent agent.
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Jong, N. K · 2005
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Discrete quantum walks hit exponentially faster
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Abstraction in Artificial Intelligence and Complex Systems (Springer, New York, NY, USA, 2013)
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Feature reinforcement learning: State of the art
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Quantum speed-up for active learning agents
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Projective simulation applied to the grid-world and the mountain-car problem
Melnikov, A. A., Makmal, A. & Briegel, H. J · 2014
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Human-level control through deep reinforcement learning
Mnih, V. et al · 2015
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Quantum walks can find a marked element on any graph
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Laumonier, J · 2007
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The logic of adaptive behavior: knowledge representation and algorithms for the Markov decision process framework in first-order domains
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An analysis of reinforcement learning with function approximation
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Feature reinforcement learning: Part I. Unstructured MDPs
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Artificial Intelligence: A Modern Approach (Prentice Hall, Englewood Cliffs, NJ, USA, 2010), third edn
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Projective simulation compared to reinforcement learning
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Evaluation and extensions of generalization in the projective simulation model
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Robotic playing for hierarchical complex skill learning
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Active learning machine learns to create new quantum experiments
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