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Found 6 papers, 1 papers with code
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics
Robots are still limited to controlled conditions, that the robot designer knows with enough details to endow the robot with the appropriate models or behaviors.
How to reduce computation time while sparing performance during robot navigation? A neuro-inspired architecture for autonomous shifting between model-based and model-free learning
We present a novel arbitration mechanism between learning systems that explicitly measures performance and cost.
Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays
The Dyna reinforcement learning algorithms use off-line replays to improve learning.
Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving task
We found that the behavior of the five monkeys was better explained in terms of a combination of RL and WM despite inter-individual differences.
A biologically constrained model of the whole basal ganglia addressing the paradoxes of connections and selection
Here we introduce a theoretical study that reconciles both views on the intra-pallidal projection, by providing a plausible characterization of the relationship between the external and internal globus pallidus.
Multi-objective analysis of computational models
A neurocomputational model of the Basal Ganglia brain nuclei is then considered and its most salient features according to this methodology are presented and discussed.
