Abstract
Future Smart-Home device usage prediction is a very important module in artificial intelligence. The technique involves analyzing the user performed actions history and apply mathematical methods to predict the most feasible next user action. Unfortunately most of the techniques tend to ignore the adaptation to the user preferred actions and the relation between the actions and the state of the environment which is not practical for Smart-Home systems. This paper present a new algorithm of user action prediction based on pattern matching and techniques of reinforcement learning. The algorithm is modeled using hardware description language VHDL. Synthetic data had been used to test the algorithm and the result shows that the algorithm performs realistically better than the current available techniques.
Original language | English |
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Title of host publication | Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications |
Publisher | CSREA |
Pages | 213-218 |
Number of pages | 6 |
ISBN (Print) | 9781601320728 |
Publication status | Published - 2008 |
Event | 2008 International Conference on Artificial Intelligence and 2008 International Conference on Machine Learning; Models, Technologies and Applications - Las Vegas, NV, United States Duration: 14 Jul 2008 → 17 Jul 2008 |
Conference
Conference | 2008 International Conference on Artificial Intelligence and 2008 International Conference on Machine Learning; Models, Technologies and Applications |
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Abbreviated title | ICAI 2008 and MLMTA 2008 |
Country/Territory | United States |
City | Las Vegas, NV |
Period | 14/07/08 → 17/07/08 |
Keywords
- Action prediction
- Multi-agent system
- Reinforcement learning
- Smart home
ASJC Scopus subject areas
- Artificial Intelligence
- Computational Theory and Mathematics
- Software
- Computer Science Applications