TY - GEN
T1 - Learning agents' relations in interactive multiagent dynamic influence diagrams
AU - Pan, Yinghui
AU - Zeng, Yifeng
AU - Mao, Hua
N1 - Publisher Copyright:
© 2015 Springer International Publishing Switzerland.
PY - 2015
Y1 - 2015
N2 - Solving interactive multiagent decision making problems is a challenging task since it needs to model how agents interact over time. From individual agents' perspective, interactive dynamic influence diagrams (I-DIDs) provide a general framework for sequential multiagent decision making in uncertain settings. Most of the current I-DID research focuses on the setting of n = 2 agents, which limits its general applications. This paper extends I-DIDs for n > 2 agents, which as expected increases the solution complexity due to the model space of other agents in the extended I-DIDs. We exploit data of agents' interactions to discover their relations thereby reducing the model complexity. We show preliminary results of the proposed techniques in one problem domain.
AB - Solving interactive multiagent decision making problems is a challenging task since it needs to model how agents interact over time. From individual agents' perspective, interactive dynamic influence diagrams (I-DIDs) provide a general framework for sequential multiagent decision making in uncertain settings. Most of the current I-DID research focuses on the setting of n = 2 agents, which limits its general applications. This paper extends I-DIDs for n > 2 agents, which as expected increases the solution complexity due to the model space of other agents in the extended I-DIDs. We exploit data of agents' interactions to discover their relations thereby reducing the model complexity. We show preliminary results of the proposed techniques in one problem domain.
KW - Intelligent agents
KW - Interactive dynamic influence diagrams
KW - Relation learning
UR - http://www.scopus.com/inward/record.url?scp=84958549834&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-20230-3_1
DO - 10.1007/978-3-319-20230-3_1
M3 - Conference contribution
AN - SCOPUS:84958549834
T3 - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
SP - 1
EP - 11
BT - Agents and Data Mining Interaction - 10th International Workshop, ADMI 2014, Revised Selected Papers
A2 - Symeonidis, Andreas L.
A2 - Zeng, Yifeng
A2 - Cao, Longbing
A2 - Gorodetsky, Vladimir
A2 - An, Bo
A2 - Coenen, Frans
A2 - Yu, Philip S.
A2 - Zeng, Yifeng
PB - Springer
T2 - 10th International Workshop on Agents and Data Mining Interaction, ADMI 2014, Held jointly with International Workshop on Autonomous Agents and Multiagent Systems, AAMAS 2014
Y2 - 5 May 2014 through 9 May 2014
ER -