6 citations · 18 across the 11 of their papers we have counts for
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Towards Model-based Reinforcement Learning for Industry-near Environments
Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo
Deep reinforcement learning has over the past few years shown great potential in learning near-optimal control in complex simulated environments with little visible information. Ra…
A Neural Turing~Machine for Conditional Transition Graph Modeling
Mehdi Ben Lazreg, Morten Goodwin, Ole-Christoffer Granmo
Graphs are an essential part of many machine learning problems such as analysis of parse trees, social networks, knowledge graphs, transportation systems, and molecular structures.…
Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games
Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo
Reinforcement learning (RL) is an area of research that has blossomed tremendously in recent years and has shown remarkable potential for artificial intelligence based opponents in…
FlashRL: A Reinforcement Learning Platform for Flash Games
Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo
Reinforcement Learning (RL) is a research area that has blossomed tremendously in recent years and has shown remarkable potential in among others successfully playing computer game…
Towards a Deep Reinforcement Learning Approach for Tower Line Wars
Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo
There have been numerous breakthroughs with reinforcement learning in the recent years, perhaps most notably on Deep Reinforcement Learning successfully playing and winning relativ…
Adaptive Task Assignment in Online Learning Environments
Per-Arne Andersen, Christian Kråkevik, Morten Goodwin +1
With the increasing popularity of online learning, intelligent tutoring systems are regaining increased attention. In this paper, we introduce adaptive algorithms for personalized…