Cooperating agents: a unified theory of communication and social structure
Distributed artificial intelligence: vol. 2
Controlling cooperative problem solving in industrial multi-agent systems using joint intentions
Artificial Intelligence
Collaborative plans for complex group action
Artificial Intelligence
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Logics of Mental Attitudes in AI
Foundation of Knowledge Representation and Reasoning [the book grew out of an ECAI-92 workshop]
MAAMAW '92 Selected papers from the 4th European Workshop on on Modelling Autonomous Agents in a Multi-Agent World, Artificial Social Systems
Reactive and Motivational Agents: Towards a Collective Minder
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
Journal of Artificial Intelligence Research
The RoboCup synthetic agent challenge 97
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Agent architectures for flexible, practical teamwork
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Preventing design conflicts in distributed design systems composed of heterogeneous agents
Engineering Applications of Artificial Intelligence
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In this paper, we propose a teamwork model based on the concept of a mental attribute called attitude. Our team model presents team as a collective abstract attitude, in which is embedded a novel way of solving problems and conflicts in our domain. We argue that this collective attitude is further decomposed into the individual attitudes of the agents towards various team attributes. We then evaluate the team problem solving behaviours of the agents in a simulated fire world using teams with and without different types of attitudes. The application and implementation of this model to a virtual fire world has revealed a promising prospect in developing team agents.