Behavior Selection System for Human–Robot Cooperation using Tensor SOM
- 10.2991/jrnal.k.200528.002How to use a DOI?
- Strategy; self-organizing map; team behavior; Tensor SOM; multi-agent system; human–robot cooperation
With the progress of technology, the realization of a symbiotic society with human beings and robots sharing the same environment has become an important subject. An example of this kind of systems is soccer game. Soccer is a multi-agent game that requires strategies by taking into account each member’s position and actions. In this paper, we discuss the results of the development of a learning system that uses self-organizing map to select behaviors depending on the situation. A set of possible actions in soccer game is decided in advance and the algorithm is able to select the best option, given some specific conditions.
- © 2020 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Moeko Tominaga AU - Yasunori Takemura AU - Kazuo Ishii PY - 2020 DA - 2020/06/02 TI - Behavior Selection System for Human–Robot Cooperation using Tensor SOM JO - Journal of Robotics, Networking and Artificial Life SP - 81 EP - 85 VL - 7 IS - 2 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.k.200528.002 DO - 10.2991/jrnal.k.200528.002 ID - Tominaga2020 ER -