1 citations · 1 across the 1 of their papers we have counts for
3 papers
Combining imagination and heuristics to learn strategies that generalize
Erik J Peterson, Necati Alp Müyesser, Timothy Verstynen +1
Deep reinforcement learning can match or exceed human performance in stable contexts, but with minor changes to the environment artificial networks, unlike humans, often cannot ada…
The Sprague-Grundy function for some selective compound games
Calvin Beideman, Matthew Bowen, Necati Alp Muyesser
We analyze the Sprague-Grundy functions for a class of almost disjoint selective compound games played on Nim heaps. Surprisingly, we find that these functions behave chaotically f…
Learning model-based strategies in simple environments with hierarchical q-networks
Necati Alp Muyesser, Kyle Dunovan, Timothy Verstynen
Recent advances in deep learning have allowed artificial agents to rival human-level performance on a wide range of complex tasks; however, the ability of these networks to learn g…