Viewing Fish Schools from an Information Science Perspective
In this research, fish schools are modeled as distributed systems composed of many agents that act based on local information. Their collective behavior is analyzed using mathematical models and computer simulations. Although the target is fish, the core focus lies on fundamental structures of information science: information acquisition, decision-making, and action.
Fish schools exhibit coherent and organized motion despite the absence of centralized control. This property is shared with multi-agent systems, swarm control, and decentralized algorithms, allowing students to learn key concepts of information science through biological phenomena.
Problem Settings Close to Real Environments: Set Nets
In real fisheries, fish do not swim in open, unconstrained spaces. Instead, they move within environments surrounded by structures such as set nets. Multiple species often enter a set net simultaneously, and undesired fish must later be separated manually, which poses practical challenges.
Motivated by this background, this research addresses the problem of how fish with different characteristics form collective structures within constrained environments. By incorporating realistic environmental conditions into the model, abstract swarm behavior models are analyzed in settings closer to real-world problems.
What Information Do Fish Use to Move?
Each individual determines its direction of motion based on limited information, such as the distance and orientation of nearby fish and its relative position to the net. In this research, basic interactions—repulsion, alignment, and attraction—are explicitly described using mathematical expressions.
In addition, behaviors such as approaching or avoiding set nets are included in the model to represent interactions between individuals and their environment. This modeling approach clarifies which information is used for decision-making, sharing a common philosophy with control modeling and algorithm design.
What Happens When Different Individuals Mix?
In real fish schools, individuals do not necessarily share identical capabilities or characteristics. Differences in swimming speed or field of view can significantly affect the collective behavior of the group.
Through simulations, it has been observed that fish schools do not simply mix uniformly; instead, they may separate by type, or one group may be attracted to another, resulting in time-varying collective structures. A key focus of this research is how small differences at the individual level influence the behavior of the entire group.
Indirect Control through the Environment
While it is not possible to directly command fish, it is possible to influence their collective behavior by adjusting environmental conditions. Changes in the shape or placement of set nets, as well as external stimuli, can alter how fish gather and move.
In this research, such environmental factors are regarded as control inputs, and the possibility of guiding the collective behavior of fish schools toward desired outcomes is explored. This perspective connects to information science challenges such as swarm robotics and environment-mediated control, which address how to handle systems that cannot be directly controlled.
An Entry Point for Students
This research theme covers the entire process from mathematical modeling and algorithm design to simulation through programming, visualization, and analysis of results. No prior background in biology is required; students can engage with this topic using foundational knowledge in information science.
The workflow of abstracting real-world problems into models and understanding behavior through computation directly aligns with what students learn in information science programs. For those who enjoy writing code while thinking about the structure of complex systems, this is a research topic that offers a natural entry point.