A Blackboard Based Hybrid Multi-Agent System for Improving Classification Accuracy Using Reinforcement Learning Techniques

Vasileios Manousakis Kokorakis, Miltos Petridis, Stelios Kapetanakis. A Blackboard Based Hybrid Multi-Agent System for Improving Classification Accuracy Using Reinforcement Learning Techniques. In Max Bramer, Miltos Petridis, editors, Artificial Intelligence XXXIV - 37th SGAI International Conference on Artificial Intelligence, AI 2017, Cambridge, UK, December 12-14, 2017, Proceedings. Volume 10630 of Lecture Notes in Computer Science, pages 47-57, Springer, 2017. [doi]

@inproceedings{KokorakisPK17,
  title = {A Blackboard Based Hybrid Multi-Agent System for Improving Classification Accuracy Using Reinforcement Learning Techniques},
  author = {Vasileios Manousakis Kokorakis and Miltos Petridis and Stelios Kapetanakis},
  year = {2017},
  doi = {10.1007/978-3-319-71078-5_4},
  url = {https://doi.org/10.1007/978-3-319-71078-5_4},
  researchr = {https://researchr.org/publication/KokorakisPK17},
  cites = {0},
  citedby = {0},
  pages = {47-57},
  booktitle = {Artificial Intelligence XXXIV - 37th SGAI International Conference on Artificial Intelligence, AI 2017, Cambridge, UK, December 12-14, 2017, Proceedings},
  editor = {Max Bramer and Miltos Petridis},
  volume = {10630},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-71078-5},
}