MARL model replicates fish collective behavior and social foraging

Researchers have developed a novel computational framework to study collective behavior in weakly electric fish using multi-agent reinforcement learning (MARL). This model successfully replicates key aspects of real fish behavior, including foraging patterns and electric organ discharge statistics. The framework allows for in silico interventions to understand the drivers of social foraging and analyzes neural dynamics to reveal how task-relevant information and social context are encoded. AI

IMPACT Provides a new simulation tool for studying animal collective behavior and emergent properties in MARL systems.

RANK_REASON Academic paper detailing a new computational framework and simulation results. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• Hugging Face
• Multi-agent reinforcement learning
• Satpreet H Singh

• paper
• other

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