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Using a network representation at different levels (social embedding and information), we have built a framework for social agents where reasoning is explicitly represented.
We used abstract argumentation and argumentative theory of reasoning to build agents that exchange information through simulated dialogues.
We demonstrated that our approach is, in principle, sufficient to reproduce two macro behaviors embedded in Granovetter’s theory, i.e., the tendency to inclusion of weak ties and a competitive advantage for non-isolated caves.
Our framework explicitly models agents reasoning capabilities and can be applied to socially embedded and interacting agents.
- represents a way for qualitative approaches to fit ABM formal requirements;
- envisages possible new grounds for cross￼fertilization between computer sciences