TY - GEN
T1 - Strategy for learning cooperative behavior with local information for multi-agent systems
AU - Uwano, Fumito
AU - Takadama, Keiki
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number JP17J08724.
Publisher Copyright:
© Springer Nature Switzerland AG 2018.
PY - 2018
Y1 - 2018
N2 - Toward learning cooperative behavior for any number of agents, this paper proposes a multi-agent reinforcement learning method without communication, called PMRL-based Learning for Any number of Agents (PLAA). PLAA prevents from agents reaching the purpose for spending too many times, and to promote the local multi-agent cooperation without communication by PMRL as a previous method. To guarantee the effectiveness of PLAA, this paper compares PLAA with Q-learning, and two previous methods in 10 kinds of the maze for the 2 and 3 agents. From the experimental result, we revealed those things: (a) PLAA is the most effective method for cooperation among 2 and 3 agents; (b) PLAA enable the agents to cooperate with each other in small iterations.
AB - Toward learning cooperative behavior for any number of agents, this paper proposes a multi-agent reinforcement learning method without communication, called PMRL-based Learning for Any number of Agents (PLAA). PLAA prevents from agents reaching the purpose for spending too many times, and to promote the local multi-agent cooperation without communication by PMRL as a previous method. To guarantee the effectiveness of PLAA, this paper compares PLAA with Q-learning, and two previous methods in 10 kinds of the maze for the 2 and 3 agents. From the experimental result, we revealed those things: (a) PLAA is the most effective method for cooperation among 2 and 3 agents; (b) PLAA enable the agents to cooperate with each other in small iterations.
UR - http://www.scopus.com/inward/record.url?scp=85056485163&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85056485163&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-03098-8_54
DO - 10.1007/978-3-030-03098-8_54
M3 - Conference contribution
AN - SCOPUS:85056485163
SN - 9783030030971
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 663
EP - 670
BT - PRIMA 2018
A2 - Oren, Nir
A2 - Sakurai, Yuko
A2 - Noda, Itsuki
A2 - Cao Son, Tran
A2 - Miller, Tim
A2 - Savarimuthu, Bastin Tony
PB - Springer Verlag
T2 - 21st International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2018
Y2 - 29 October 2018 through 2 November 2018
ER -