Date of Publication :20th December 2017

Abstract: Agent-Based Model (ABM) is a class of computational models for simulating the actions and interactions of autonomous agents with a view to accessing their effects on the system as a whole. It combines elements of game theory, complex system, emergence, computational sociology, multi-agent system and evolutionary programming. ABMs are also called individual-based models (IBMs). ABMs are a kind of micro sale model that simulate the simultaneous operations and interactions of multiple agents to re-create and predict the appearance of complex phenomena. The key notion is that simple behavioral rules generate complex behavior. Most Agent-Based Models are composed of numerous agents specified at various scales, Decision-making heuristics, Learning rules or adaptive processes, An interaction topology, Non-agent environment. ABMs are typically implemented as computer simulations, either as custom software or via ABM toolkit, and this software can be used to test how changes in individual behavior will affect the system’s emerging overall behavior. This paper presents an overview of how agents communicate agent communication languages and interaction protocols.

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