514 citations · 522 across the 3 of their papers we have counts for
3 papers · 1 filter
The configurable tree graph (CT-graph): measurable problems in partially observable and distal reward environments for lifelong reinforcement learning
Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Christos Peridis +4
This paper introduces a set of formally defined and transparent problems for reinforcement learning algorithms with the following characteristics: (1) variable degrees of observabi…
Exploration in Deep Reinforcement Learning: A Survey
Pawel Ladosz, Lilian Weng, Minwoo Kim +1
This paper reviews exploration techniques in deep reinforcement learning. Exploration techniques are of primary importance when solving sparse reward problems. In sparse reward pro…
Deep Reinforcement Learning with Modulated Hebbian plus Q Network Architecture
Pawel Ladosz, Eseoghene Ben-Iwhiwhu, Jeffery Dick +6
This paper presents a new neural architecture that combines a modulated Hebbian network (MOHN) with DQN, which we call modulated Hebbian plus Q network architecture (MOHQA). The hy…