Enhancing multi-agent based simulation with human-like decision making strategies
MABS 2000 Proceedings of the second international workshop on Multi-agent based simulation
ANALYSIS OF ASYNCHRONOUS CONCURRENT SYSTEMS BY TIMED PETRI NETS
ANALYSIS OF ASYNCHRONOUS CONCURRENT SYSTEMS BY TIMED PETRI NETS
Folk Psychology for Human Modelling: Extending the BDI Paradigm
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Extending the recognition-primed decision model to support human-agent collaboration
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
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The Recognition-Primed Decision (RPD) framework is a naturalistic decision making model that focuses on how people actually make decisions in realistic settings that typically involve ill-structured problems. In this paper, we generalize the existing studies on RPD and propose a Team-RPD representation model that treats a situation as a layered organization of state variables, and the decision process as a timed transition Petri net. This model can serve as a foundation for implementing agent architectures and multi-agent systems with built-in supports for naturalistic decision making.