Parallel DEVS: a parallel, hierarchical, modular, modeling formalism
WSC '94 Proceedings of the 26th conference on Winter simulation
WSC '95 Proceedings of the 27th conference on Winter simulation
AgentSpeak(L): BDI agents speak out in a logical computable language
MAAMAW '96 Proceedings of the 7th European workshop on Modelling autonomous agents in a multi-agent world : agents breaking away: agents breaking away
Computer science as empirical inquiry: symbols and search
Communications of the ACM
"Plug and test": software agents in virtual environments
Proceedings of the 32nd conference on Winter simulation
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Theory of Modeling and Simulation
Theory of Modeling and Simulation
A Formal Specification of dMARS
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Support to decision makers: the use of recursive simulation to support decisionmaking
Proceedings of the 35th conference on Winter simulation: driving innovation
Formal specification supporting incremental and flexible agent-based modeling
Proceedings of the Winter Simulation Conference
A DEVS-based M&S method for large-scale multi-agent systems
Proceedings of the 2013 Summer Computer Simulation Conference
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Analysing and designing whole-farm systems can greatly be enhanced by using simulation platforms that support representation of management decision-making processes. As manager of a purposive system, a farmer reasons his actions on the basis of a deliberated context-dependent course of actions setup to integrate biological, managerial and technical constraints specific to the farm and its environment. This paper presents a system-based model of such deliberative decision-making behavior based on the DEVS (Discrete Event System Specification) formalism. The modeling of farmer's decision-making is addressed using the Belief-Desire-Intention (BDI) agent paradigm that provides a theoretical framework to articulate respectively the informational, motivational and intentional drivers underlying decision-making in an open (dynamic) environment. The functioning of such a management process is illustrated through the example of scheduling and coordinating the technical activities involved in a corn production system.