Introduction to Multiagent Systems
Introduction to Multiagent Systems
A Study of Organizational Learning in Multi-Agent Sytems
ECAI '96 Selected papers from the Workshop on Distributed Artificial Intelligence Meets Machine Learning, Learning in Multi-Agent Environments
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Validation and verification of simulation models
WSC '04 Proceedings of the 36th conference on Winter simulation
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
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A team's task process consists of allocation, processing and evaluation of a series of tasks. Team effectiveness emerges from interactions among team members. The interactions between the task process and members occur when team allocates and processes tasks. To address the effect of the interaction on team effectiveness, Multi-agent based modelling and simulation is utilized to develop a multi-agent model of team's task process, in which we put forward member relation degree and member-task matching degree to describe the social relations existing in a team and how members' competence match with tasks' demands respectively. We implement the model by Repast J and conduct experiments to validate the model using face validation technique in an actual Chinese team. The implication of the model to the team is discussed and some suggestions are offered. The conclusion is given at last.