74 citations · 82 across the 5 of their papers we have counts for
5 papers
A general Markov decision process formalism for action-state entropy-regularized reward maximization
Dmytro Grytskyy, Jorge Ramírez-Ruiz, Rubén Moreno-Bote
Previous work has separately addressed different forms of action, state and action-state entropy regularization, pure exploration and space occupation. These problems have become e…
Complex behavior from intrinsic motivation to occupy action-state path space
Jorge Ramírez-Ruiz, Dmytro Grytskyy, Chiara Mastrogiuseppe +2
Most theories of behavior posit that agents tend to maximize some form of reward or utility. However, animals very often move with curiosity and seem to be motivated in a reward-fr…
A learning rule balancing energy consumption and information maximization in a feed-forward neuronal network
Dmytro Grytskyy, Renaud B. Jolivet
Information measures are often used to assess the efficacy of neural networks, and learning rules can be derived through optimization procedures on such measures. In biological neu…
A reaction diffusion-like formalism for plastic neural networks reveals dissipative solitons at criticality
Dmytro Grytskyy, Markus Diesmann, Moritz Helias
Self-organized structures in networks with spike-timing dependent plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study…
A unified view on weakly correlated recurrent networks
Dmytro Grytskyy, Tom Tetzlaff, Markus Diesmann +1
The diversity of neuron models used in contemporary theoretical neuroscience to investigate specific properties of covariances raises the question how these models relate to each o…