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Data · dataset · 2023

Data Modelling and visual representation for Collective Perception

Listed in Teesside University Research Data Repository

Model Components: 1.

Description

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.

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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.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Design 70% · Simulation 75%
Provenance · 1 source records, 14 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/fzrkf8z5j5.112 d agoJSON v1
FieldAssertionExtractorEvidence
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