Reinforcement Learning in non-stationary environments: An intrinsically motivated stress based memory retrieval performance (SBMRP) model

Tiong Yew Tang, Simon Egerton, Naoyuki Kubota. Reinforcement Learning in non-stationary environments: An intrinsically motivated stress based memory retrieval performance (SBMRP) model. In IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014, Beijing, China, July 6-11, 2014. pages 1728-1735, IEEE, 2014. [doi]

@inproceedings{TangEK14,
  title = {Reinforcement Learning in non-stationary environments: An intrinsically motivated stress based memory retrieval performance (SBMRP) model},
  author = {Tiong Yew Tang and Simon Egerton and Naoyuki Kubota},
  year = {2014},
  doi = {10.1109/FUZZ-IEEE.2014.6891757},
  url = {http://dx.doi.org/10.1109/FUZZ-IEEE.2014.6891757},
  researchr = {https://researchr.org/publication/TangEK14},
  cites = {0},
  citedby = {0},
  pages = {1728-1735},
  booktitle = {IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014, Beijing, China, July 6-11, 2014},
  publisher = {IEEE},
}