A Modelling Approach Based on Fuzzy Agents
This work addresses modeling challenges for systems with imprecision or subjectivity, but it appears incremental as it redefines existing agent architectures.
The paper tackles the problem of modeling complex systems with uncertainty by introducing the concept of fuzzy agents, which combine agent-based modeling with fuzzy logic, and illustrates this with a smart watering system example.
Modelling of complex systems is mainly based on the decomposition of these systems in autonomous elements, and the identification and definitio9n of possible interactions between these elements. For this, the agent-based approach is a modelling solution often proposed. Complexity can also be due to external events or internal to systems, whose main characteristics are uncertainty, imprecision, or whose perception is subjective (i.e. interpreted). Insofar as fuzzy logic provides a solution for modelling uncertainty, the concept of fuzzy agent can model both the complexity and uncertainty. This paper focuses on introducing the concept of fuzzy agent: a classical architecture of agent is redefined according to a fuzzy perspective. A pedagogical illustration of fuzzy agentification of a smart watering system is then proposed.