Sales Time Series Analytics Using Deep Q-Learning

L.-J. Lin, “Reinforcement learning for robots using neural networks,” tech. rep., Carnegie-Mellon Univ Pittsburgh PA School of Computer Science, 1993

1993

Earlier work this paper cites.

MIT press Cambridge, 1998

R. S. Sutton, A. G. Barto, et al · 1998

Earlier work this paper cites.

C. Raju, Y. Narahari, and K. Ravikumar, “Reinforcement learning applications in dynamic pricing of retail markets,” in EEE International Conference on E-Commerce, 2003. CEC 2003

2003

Earlier work this paper cites.

John Wiley & Sons, 2005

R. S. Tsay, Analysis of financial time series · 2005

Earlier work this paper cites.

C. O. Kim, J. Jun, J. Baek, R. Smith, and Y.-D. Kim, “Adaptive inventory control models for supply chain management,” The International Journal of Advanced Manufacturing Technology

2005

Earlier work this paper cites.

F. Liu, C. Quek, and G. S. Ng, “Neural network model for time series prediction by reinforcement learning,” in Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005

2005

Earlier work this paper cites.

P. Doganis, A. Alexandridis, P. Patrinos, and H. Sarimveis, “Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing,” Journal of Food Engineering

2006

Earlier work this paper cites.

D. Vengerov, “A gradient-based reinforcement learning approach to dynamic pricing in partially-observable environments,” 2007

2007

Earlier work this paper cites.

V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller, “Playing atari with deep reinforcement learning,” arXiv preprint arXiv:1312.5602

Original

2013

Earlier work this paper cites.

R. Rana and F. S. Oliveira, “Real-time dynamic pricing in a non-stationary environment using model-free reinforcement learning,” Omega

2014

Cited alongside, same era.

John Wiley & Sons, 2015

G. E. Box, G. M. Jenkins, G. C. Reinsel, and G. M. Ljung, Time series analysis: forecasting and control · 2015

Cited alongside, same era.

V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, et al

2015

Cited alongside, same era.

A. V. den Boer, “Dynamic pricing and learning: historical origins, current research, and new directions,” Surveys in operations research and management science

2015

Cited alongside, same era.

G. Dulac-Arnold, R. Evans, H. van Hasselt, P. Sunehag, T. Lillicrap, J. Hunt, T. Mann, T. Weber, T. Degris, and B. Coppin, “Deep reinforcement learning in large discrete action spaces,” arXiv preprint arXiv:1512.07679

Original

2015

B. Pavlyshenko, “Using stacking approaches for machine learning models,” in 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP)

2018

Later among the works it cites.

R. Maestre, J. Duque, A. Rubio, and J. Arévalo, “Reinforcement learning for fair dynamic pricing,” in Proceedings of SAI Intelligent Systems Conference

2018

Later among the works it cites.

C. Y. Huang, “Financial trading as a game: A deep reinforcement learning approach,” arXiv preprint arXiv:1807.02787

Original

2018

Later among the works it cites.

B. M. Pavlyshenko, “Machine-learning models for sales time series forecasting,” Data

2019

Later among the works it cites.

On-line resource, accessed 5 December 2019

“Github Repository.” https://github.com/dennybritz/reinforcement-learning · 2019

Later among the works it cites.