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What Types of Interactions do Bio-Inspired Robot Swarms and Flocks Afford a Human?

Abstract

"This paper uses simulations to identify what types of human influence are afforded by the flocking and swarming structures that emerge from Couzin's bio-inspired model. The goal is to allow a human to influence a decentralized agent collective without resorting to centralized human control. Evidence is provided that, when nominal agents use switching-based control to respond to human-guided predators and leaders, the resulting behavior is responsive to human input but is obtained at the cost of causing the dynamic structure of the collective to follow a single flocking structure. Leaders are more effective in influencing coherent flocks, but predators can be used to divide the flock into sub-flocks, yielding higher performance on some problems. Introducing a so-called ""stakeholder"" leadership style makes it possible for a human to guide the agents while maintaining several different types of structures; doing so requires more than one human-controlled agent. We then demonstrate that it is possible to produce potentially useful emergent dynamics without centralized human control, and identify an important type of emergent dynamics: automatic switches between structure types."

The Questioner
🌱 Topic Pioneer — Trajectory Prediction
📈 Trend Setter — Multi-Agent Systems
🧭 Keyword Pioneer — collective behavior
🐝 Cross-Pollinator — Artificial Intelligence, Deep Learning, Machine Learning, Mathematics & Optimization, Reinforcement Learning, Robotics
🌉 Interdisciplinary Bridge — Artificial Intelligence and Reinforcement Learning and Robotics
🐣 Hot Topic Early Bird — multi-agent system