Search Results for author:
Found 5 papers, 3 papers with code
Procedurally generating rules to adapt difficulty for narrative puzzle games
This paper focuses on procedurally generating rules and communicating them to players to adjust the difficulty.
Safer Reinforcement Learning through Transferable Instinct Networks
Random exploration is one of the main mechanisms through which reinforcement learning (RL) finds well-performing policies.
Growing 3D Artefacts and Functional Machines with Neural Cellular Automata
Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells.
EvoCraft: A New Challenge for Open-Endedness
In contrast to previous work in Minecraft that focused on learning to play the game, the grand challenge we pose here is to automatically search for increasingly complex artifacts in an open-ended fashion.
Safe Reinforcement Learning through Meta-learned Instincts
Here we introduce a novel approach called Meta-Learned Instinctual Networks (MLIN) that allows agents to safely learn during their lifetime while avoiding potentially hazardous states.
