5 citations · 7 across the 4 of their papers we have counts for
4 papers · 1 filter
Navigating Demand Uncertainty in Container Shipping: Deep Reinforcement Learning for Enabling Adaptive and Feasible Master Stowage Planning
Jaike van Twiller, Yossiri Adulyasak, Erick Delage +2
Reinforcement learning (RL) has successfully solved various deterministic and stochastic planning problems. However, conventional RL struggles with complex real-world constraints,…
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…
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…
Safe Reinforcement Learning through Meta-learned Instincts
Djordje Grbic, Sebastian Risi
An important goal in reinforcement learning is to create agents that can quickly adapt to new goals while avoiding situations that might cause damage to themselves or their environ…