134 citations · 548 across the 33 of their papers we have counts for
4 papers · 1 filter
Evolutionary learning of interpretable decision trees
Leonardo Lucio Custode, Giovanni Iacca
Reinforcement learning techniques achieved human-level performance in several tasks in the last decade. However, in recent years, the need for interpretability emerged: we want to…
EVO-RL: Evolutionary-Driven Reinforcement Learning
Ahmed Hallawa, Thorsten Born, Anke Schmeink +6
In this work, we propose a novel approach for reinforcement learning driven by evolutionary computation. Our algorithm, dubbed as Evolutionary-Driven Reinforcement Learning (evo-RL…
Distributed Embodied Evolution over Networks
Anil Yaman, Giovanni Iacca
In several network problems the optimum behavior of the agents (i.e., the nodes of the network) is not known before deployment. Furthermore, the agents might be required to adapt,…
Novelty Producing Synaptic Plasticity
Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu +2
A learning process with the plasticity property often requires reinforcement signals to guide the process. However, in some tasks (e.g. maze-navigation), it is very difficult (or i…