58 citations · 170 across the 17 of their papers we have counts for
9 papers · 1 filter
Safer Reinforcement Learning through Transferable Instinct Networks
Djordje Grbic, Sebastian Risi
Random exploration is one of the main mechanisms through which reinforcement learning (RL) finds well-performing policies. However, it can lead to undesirable or catastrophic outco…
Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning
Mathias Löwe, Jennifer Villareale, Evan Freed +3
Applying neural network (NN) methods in games can lead to various new and exciting game dynamics not previously possible. However, they also lead to new challenges such as the lack…
Fast Game Content Adaptation Through Bayesian-based Player Modelling
Miguel González-Duque, Rasmus Berg Palm, Sebastian Risi
In games, as well as many user-facing systems, adapting content to users' preferences and experience is an important challenge. This paper explores a novel method to realize this g…
Evolving and Merging Hebbian Learning Rules: Increasing Generalization by Decreasing the Number of Rules
Joachim Winther Pedersen, Sebastian Risi
Generalization to out-of-distribution (OOD) circumstances after training remains a challenge for artificial agents. To improve the robustness displayed by plastic Hebbian neural ne…
Rapid Risk Minimization with Bayesian Models Through Deep Learning Approximation
Mathias Löwe, Per Lunnemann Hansen, Sebastian Risi
We introduce a novel combination of Bayesian Models (BMs) and Neural Networks (NNs) for making predictions with a minimum expected risk. Our approach combines the best of both worl…
Growing 3D Artefacts and Functional Machines with Neural Cellular Automata
Shyam Sudhakaran, Djordje Grbic, Siyan Li +4
Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells. Re…