TY - GEN
T1 - Cluster Formation in Multiagent Consensus via Dynamic Resilient Graph Games
AU - Nugraha, Yurid
AU - Cetinkaya, Ahmet
AU - Hayakawa, Tomohisa
AU - Ishii, Hideaki
AU - Zhu, Quanyan
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In this paper we formulate a two-player game-theoretic problem on resilient graphs representing communication channels that are vulnerable to attacks in multiagent consensus setting. An attacker is capable to disconnect part of the edges of the graph by emitting jamming signals while, in response, the defender recovers some of them by increasing the transmission power for the communication signals over the corresponding edges. It is also possible for the attacker to emit stronger jamming signals that cannot be overcome by the defender. We consider repeated games where the utilities of players in each game depend on attack/recovery performance measured over multiple intervals. The utilities of both players are mainly related to agents' states and the cluster formation, i.e., how the agents are divided. The players' actions are constrained by their energy for transmissions, with a less strict constraint for the attacker compared to the defender. Numerical examples of dynamic games played over time are provided to demonstrate the cluster formation.
AB - In this paper we formulate a two-player game-theoretic problem on resilient graphs representing communication channels that are vulnerable to attacks in multiagent consensus setting. An attacker is capable to disconnect part of the edges of the graph by emitting jamming signals while, in response, the defender recovers some of them by increasing the transmission power for the communication signals over the corresponding edges. It is also possible for the attacker to emit stronger jamming signals that cannot be overcome by the defender. We consider repeated games where the utilities of players in each game depend on attack/recovery performance measured over multiple intervals. The utilities of both players are mainly related to agents' states and the cluster formation, i.e., how the agents are divided. The players' actions are constrained by their energy for transmissions, with a less strict constraint for the attacker compared to the defender. Numerical examples of dynamic games played over time are provided to demonstrate the cluster formation.
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U2 - 10.1109/CCTA48906.2021.9659182
DO - 10.1109/CCTA48906.2021.9659182
M3 - Conference contribution
AN - SCOPUS:85124791912
T3 - CCTA 2021 - 5th IEEE Conference on Control Technology and Applications
SP - 735
EP - 740
BT - CCTA 2021 - 5th IEEE Conference on Control Technology and Applications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE Conference on Control Technology and Applications, CCTA 2021
Y2 - 8 August 2021 through 11 August 2021
ER -