Barry Nichols

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  1. Nichols, Barry D. ORCID: https://orcid.org/0000-0002-6760-6037 (2017) A comparison of eligibility trace and momentum on SARSA in continuous state- and action-space. In: 9th Computer Science & Electronic Engineering Conference (CEEC 2017), 27-29 Sep 2017, Colchester, UK.
  2. Nichols, Barry D. ORCID: https://orcid.org/0000-0002-6760-6037 (2016) A comparison of action selection methods for implicit policy method reinforcement learning in continuous action-space. In: International Joint Conference on Neural Networks (IJCNN 2016), 24-29 Jul 2016, Vancouver, Canada.
  3. Nichols, Barry D. ORCID: https://orcid.org/0000-0002-6760-6037 (2015) Continuous action-space reinforcement learning methods applied to the minimum-time swing-up of the acrobot. In: Systems, Man and Cybernetics (SMC), 2015 IEEE International Conference on. Institute of Electrical and Electronics Engineers (IEEE), pp. 2084-2089. ISBN 9781479986965
  4. Dracopoulos, Dimitris C. and Nichols, Barry D. ORCID: https://orcid.org/0000-0002-6760-6037 (2017) Genetic programming for the minimum time swing up and balance control acrobot problem. Expert Systems, 34 (5). ISSN 1468-0394
  5. Dracopoulos, Dimitris C. and Nichols, Barry D. ORCID: https://orcid.org/0000-0002-6760-6037 (2012) Swing up and balance control of the acrobot solved by genetic programming. In: Research and Development in Intelligent Systems XXIX. Springer London, pp. 229-242. ISBN 9781447147381
  6. Nichols, Barry D. ORCID: https://orcid.org/0000-0002-6760-6037 and Dracopoulos, Dimitris C. (2014) Application of Newton's method to action selection in continuous state- and action-space reinforcement learning. In: ESANN 2014 Proceedings: 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges April 23-24-25, 2014. ESANN, pp. 141-146. ISBN 9782874190957
  7. Dracopoulos, Dimitris C., Effraimidis, Dimitrios and Nichols, Barry D. ORCID: https://orcid.org/0000-0002-6760-6037 (2013) Genetic programming as a solver to challenging reinforcement learning problems. In: Horizons in computer science research. Horizons in Computer Science Research, 8 . Nova Publications, Hauppauge, NY, USA, pp. 145-174.