TY - GEN
T1 - Attracted to Fish
T2 - 17th annual conference of European Social Simulation Association, ESSA 2022
AU - Payette, Nicolas
AU - Carella, Ernesto
AU - Vert-Pre, Katyana
AU - Powers, Brian
AU - Saul, Steven
AU - Drexler, Michael
AU - Ananthanarayanan, Aarthi
AU - Bailey, Richard
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - This paper presents a gravity-based behavioral algorithm designed to simulate the dynamic decision-making processes of purse seine fishers in the Eastern Pacific Ocean. The algorithm captures the complex interplay between fishers’ actions, environmental conditions, and regulatory constraints. It comprises two core strategies: an action strategy and a destination strategy. The action strategy involves selecting the most favorable course of action based on estimated values and preferences, while the destination strategy uses gravity fields to determine attractive ocean cell locations. These fields are modulated by real-time circumstances, guiding fishers toward areas of high value. Calibration against real-world data from the Inter-American Tropical Tuna Commission (IATTC) observer database is ongoing, with a focus on achieving accurate representation of action frequencies and species-specific catch per action type. Initial calibration results highlight the need for further refinement. While still a work in progress, this algorithm provides a robust foundation for capturing the intricate dynamics of purse seine fishing, adapting to evolving conditions, and informing policy evaluations. Future enhancements include adaptive fishing strategies and incorporating fleet-level interactions for a more comprehensive understanding of fishing behaviors.
AB - This paper presents a gravity-based behavioral algorithm designed to simulate the dynamic decision-making processes of purse seine fishers in the Eastern Pacific Ocean. The algorithm captures the complex interplay between fishers’ actions, environmental conditions, and regulatory constraints. It comprises two core strategies: an action strategy and a destination strategy. The action strategy involves selecting the most favorable course of action based on estimated values and preferences, while the destination strategy uses gravity fields to determine attractive ocean cell locations. These fields are modulated by real-time circumstances, guiding fishers toward areas of high value. Calibration against real-world data from the Inter-American Tropical Tuna Commission (IATTC) observer database is ongoing, with a focus on achieving accurate representation of action frequencies and species-specific catch per action type. Initial calibration results highlight the need for further refinement. While still a work in progress, this algorithm provides a robust foundation for capturing the intricate dynamics of purse seine fishing, adapting to evolving conditions, and informing policy evaluations. Future enhancements include adaptive fishing strategies and incorporating fleet-level interactions for a more comprehensive understanding of fishing behaviors.
KW - Agent-based simulation
KW - Fish aggregation devices
KW - Fisheries management
KW - Fishing behavior
KW - Gravity model
UR - http://www.scopus.com/inward/record.url?scp=85174524844&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85174524844&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-34920-1_8
DO - 10.1007/978-3-031-34920-1_8
M3 - Conference contribution
AN - SCOPUS:85174524844
SN - 9783031349195
T3 - Springer Proceedings in Complexity
SP - 87
EP - 103
BT - Advances in Social Simulation - Proceedings of the 17th Social Simulation Conference, European Social Simulation Association
A2 - Squazzoni, Flaminio
PB - Springer Science and Business Media B.V.
Y2 - 12 September 2022 through 16 September 2022
ER -