| Title: | GS2-1 Adaptive Negotiation-rules Acquisition Methods in Decentralized AGV Transportation Systems by Reinforcement Learning with a State Space Filter |
|---|---|
| Publication: | ICAROB2017 |
| Volume: | 22 |
| Pages: | 346-349 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2017.GS2-1 |
| Author(s): | Masato Nagayoshi, Simon Elderton, Kazutoshi Sakakibara, Hisashi Tamaki |
| Publication Date: | January 19, 2017 |
| Keywords: | reinforcement learning, AGV transportation system, negotiation rules, state space filter |
| Abstract: | In this paper, we introduce an autonomous decentralized method for multiple Automated Guided Vehicles (AGVs). In our proposed system, each AGV as an agent computes its transportation route by referring to the static path information. route. Once potential collisions are detected, one of the two agents chosen by a negotiation rule modifies its route plan. The rules are improved by reinforcement learning with a state space filter. Then, the performance is confirmed with regard to the adaptive negotiation rules. |
| PDF File: | https://alife-robotics.co.jp/members2017/icarob/data/html/data/GS_pdf/GS2/GS2-1.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
(c)2008 Copyright The Regents of ALife Robotics Corporation Ltd. All Rights Reserved.