TY - GEN
T1 - Ev-IDID
T2 - 21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022
AU - Ma, Biyang
AU - Pan, Yinghui
AU - Zeng, Yifeng
AU - Ming, Zhong
N1 - Funding Information: Professor Yifeng Zeng received the support from the EPSRC New Investigator Award and Biyang is partially supported by the EP-SRC project (Grant No. EP/S011609/1). This work is supported in part by the National Natural Science Foundation of China (Grants No.61772442, 61836005 and 62176225).
PY - 2022
Y1 - 2022
N2 - Interactive dynamic influence diagrams (I-DIDs) are a general framework for multiagent sequential decision making under uncertainty. Due to the model complexity, a significant amount of research has been invested into solving the model through various types of either exact or approximate algorithms. However, there is no tool that allows users to specify the algorithm parameters and visualise the model solutions. In this demo, we develop an interactive I-DID system that implements most of the state-of-art I-DID algorithms and develops a new type of algorithms based on evolutionary computation. In particular, we propose a multi-population genetic algorithm for solving the I-DID models and automate the generation of behavioural models in the solutions. This demo will facilitate the I-DID research development and practical applications, and elicit a new wave of I-DID solutions based on evolutionary algorithms.
AB - Interactive dynamic influence diagrams (I-DIDs) are a general framework for multiagent sequential decision making under uncertainty. Due to the model complexity, a significant amount of research has been invested into solving the model through various types of either exact or approximate algorithms. However, there is no tool that allows users to specify the algorithm parameters and visualise the model solutions. In this demo, we develop an interactive I-DID system that implements most of the state-of-art I-DID algorithms and develops a new type of algorithms based on evolutionary computation. In particular, we propose a multi-population genetic algorithm for solving the I-DID models and automate the generation of behavioural models in the solutions. This demo will facilitate the I-DID research development and practical applications, and elicit a new wave of I-DID solutions based on evolutionary algorithms.
KW - Evolutionary Algorithms
KW - Interactive Decision Systems
KW - Interactive Dynamic Influence Diagrams
UR - http://www.scopus.com/inward/record.url?scp=85134315358&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85134315358
T3 - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
SP - 1911
EP - 1913
BT - International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Y2 - 9 May 2022 through 13 May 2022
ER -