Almond Mushroom, ABM · 2024 · Preprint
Medium relevancePerspectives: Two Approaches in Computational Social Sciences
Agaricus blazei
Key points
- Big data-driven machine learning and artificial intelligence (ML/AI) is not all computational social sciences (CSS) have
- Agent-based modeling (ABM) or multi-agent system (MAS) is another fundamentally different but equally useful approach in CSS. In fact, the two approaches start from very different orientations and their differences have deeper root in ontology
- ML/AI aims to imitate and then surpass human capacities, from sensing to perceiving, reasoning, calculating, and acting
- In contrast, ABM seeks to simulate how social outcomes emerge from the complex interactions of agents’ actions within a specific environment
- Yet, precisely because these two technologies are different, they can be complementary to each other
- There is a bright future for integrating ABM with ML/AI for tackling real world challenges
From the paper
Abstract
Big data-driven machine learning and artificial intelligence (ML/AI) is not all computational social sciences (CSS) have. Agent-based modeling (ABM) or multi-agent system (MAS) is another fundamentally different but equally useful approach in CSS. In fact, the two approaches start from very different orientations and their differences have deeper root in ontology. ML/AI aims to imitate and then surpass human capacities, from sensing to perceiving, reasoning, calculating, and acting. In contrast, ABM seeks to simulate how social outcomes emerge from the complex interactions of agents’ actions within a specific environment. Yet, precisely because these two technologies are different, they can be complementary to each other. There is a bright future for integrating ABM with ML/AI for tackling real world challenges.
Citation
Tang S (2024). Perspectives: Two Approaches in Computational Social Sciences. https://doi.org/10.20944/preprints202410.1654.v1
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