Topic: collective behavior

Many species cohesively navigate their environment as a group. This includes fish schools and shoals, where group structure emerges from social interactions, which can subsequently facilitate adaptive advantages such as collective foraging. While previous work has characterized how group structure emerges from social interactions, less is known about how collective behavior is influenced by external factors (e.g., resource availability) and internal physiological states (e.g., hunger), and their underlying behavioral and neural mechanisms. To address how collective behavior is influenced by bo

Social foraging is a fundamental collective behavior observed across various species, but studying complex multi-agent dynamics and accompanying neural activity in natural settings remains challenging. Here we present an in silico study of social interaction during foraging using recurrent neural network (RNN) agents trained using multi-agent reinforcement learning (MARL). Our framework explores how different group sizes, food availability, and sensory capabilities shape emergent foraging strategies in grops of 2 to 10 agents. These group sizes are especially relevant to experimental social ne