Data Modelling and visual representation for Collective Perception

Model Components: 1. Agents: Each agent has: • Attributes (e.g., perception, behaviour, memory). • Decision-making rules (e.g., follow majority, imitate successful agents). • Perception of stimuli (e.g., based on neighbours' actions or external information). 2. Environment: • Space or network where agents interact. • Stimuli or signals that influence agents' perceptions. • Rules governing interaction and communication among agents. Simulation Steps: 1. Initialization: • Create a population of agents with initial attributes and perceptions. • Define the environment and initial stimuli. 2. Interaction: • Agents perceive stimuli from their environment or neighbours. • Agents update their attributes or behaviours based on perceived stimuli and predefined decision rules. • Agents interact with neighbours, influencing or being influenced by their actions. 3. Iteration: • Repeat the interaction steps for multiple time steps or iterations. • Observe how individual actions aggregate into collective behaviours. • Analyse emergent patterns, consensus, or divergence among agents.