Blar i NTNU Open på forfatter "Goodwin, Morten"

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    • ANN modelling of CO2 refrigerant cooling system COP in a smart warehouse 

      Opalic, Sven Myrdahl; Goodwin, Morten; Lei, Jiao; Nielsen, Henrik Kofoed; Pardiñas, Ángel Á.; Hafner, Armin; Kolhe, Mohan Lal (Peer reviewed; Journal article, 2020)
      Industrial cooling systems consume large quantities of energy with highly variable power demand. To reduce environmental impact and overall energy consumption, and to stabilize the power requirements, it is recommended to ...

    • Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow 

      Yazidi, Anis; Abolpour Mofrad, Asieh; Goodwin, Morten; Hammer, Hugo Lewi; Arntzen, Erik (Peer reviewed; Journal article, 2020)
      An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner ...

    • Digitalization of the power business: How to make this work? 

      Svendsen, Arne Brufladt; Tollefsen, Trond; Gjengedal, Terje; Goodwin, Morten; Antonsen, Stian (Chapter, 2018)
      As a result of the digitalization of the power business in Norway and Europa, a lot of new possibilities and challenges arise. In 2014 an expert committee one outlined a proposal for the future grid company structure in ...

    • Expert Q-learning: Deep Reinforcement Learning with Coarse State Values from Offline Expert Examples 

      Meng, Li; Yazidi, Anis; Goodwin, Morten; Engelstad, Paal (Peer reviewed; Journal article, 2022)
      In this article, we propose a novel algorithm for deep reinforcement learning named Expert Q-learning. Expert Q-learning is inspired by Dueling Q-learning and aims to incorporate semi-supervised learning into reinforcement ...

    • FlashRL: A Reinforcement Learning Platform for Flash Games 

      Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2017)
      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 games. However, there only exists a few game ...

    • Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise 

      Meng, Li; Goodwin, Morten; Yazidi, Anis; Engelstad, Paal (Peer reviewed; Journal article, 2022)
      Q-learning is one of the most well-known Reinforcement Learning algorithms. There have been tremendous efforts to develop this algorithm using neural networks. Bootstrapped Deep Q-Learning Network is amongst them. It ...