Udenze, Adrian and McDonald-Maier, Klaus (2009) Indirect Reinforcement Learning for Autonomous Power Configuration and Control in Wireless Networks. In: 2009 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), 2009-07-29 - 2009-08-01.
Udenze, Adrian and McDonald-Maier, Klaus (2009) Indirect Reinforcement Learning for Autonomous Power Configuration and Control in Wireless Networks. In: 2009 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), 2009-07-29 - 2009-08-01.
Udenze, Adrian and McDonald-Maier, Klaus (2009) Indirect Reinforcement Learning for Autonomous Power Configuration and Control in Wireless Networks. In: 2009 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), 2009-07-29 - 2009-08-01.
Abstract
In this paper, non deterministic Indirect Reinforcement Learning (RL) techniques for controlling the transmission times and power of Wireless Network nodes are presented. Indirect RL facilitates planning and learning which ultimately leads to convergence on optimal actions with reduced episodes or time steps compared to direct RL. Three Dyna architecture based algorithms for non deterministic environments are presented. The results show improvements over direct RL and conventional static power control techniques. © 2009 Crown.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Published proceedings: Proceedings - 2009 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2009 |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 18 Sep 2013 19:35 |
| Last Modified: | 30 Oct 2024 19:16 |
| URI: | http://repository.essex.ac.uk/id/eprint/6860 |