This paper brings together work in modeling episodic memory and reinforcement learning. We demonstrate that is possible to learn to use episodic memory retrievals while simultaneo...
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
Transfer learning concerns applying knowledge learned in one task (the source) to improve learning another related task (the target). In this paper, we use structure mapping, a ps...
Efficient and robust routing is central to wireless sensor networks (WSN) that feature energy-constrained nodes, unreliable links, and frequent topology change. While most existi...
Modern interactive computer games provide the ability to objectively record complex human behavior, offering a variety of interesting challenges to the pattern-recognition communi...
Bernard Gorman, Christian Bauckhage, Christian Thu...