Artificial Intelligence
Understanding agent systems
Extending Activity Diagrams to Model Mobile Systems
NODe '02 Revised Papers from the International Conference NetObjectDays on Objects, Components, Architectures, Services, and Applications for a Networked World
Modelling and Design of Multi-Agent Systems
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
Specifying Agent Interaction Protocols with Standard UML
AOSE '01 Revised Papers and Invited Contributions from the Second International Workshop on Agent-Oriented Software Engineering II
Representing Social Structures in UML
AOSE '01 Revised Papers and Invited Contributions from the Second International Workshop on Agent-Oriented Software Engineering II
From a Conceptual Framework for Agents and Objects to a Multi-Agent System Modeling Language
Autonomous Agents and Multi-Agent Systems
A UML Based Approach for Modeling and Implementing Multi-Agent Systems
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Using the UML 2.0 activity diagram to model agent plans and actions
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
UML 2.0 and agents: how to build agent-based systems with the new UML standard
Engineering Applications of Artificial Intelligence
The role of roles in designing effective agent organizations
Software engineering for large-scale multi-agent systems
Towards the modeling reactive and proactive agents by using MAS-ML
Proceedings of the 2010 ACM Symposium on Applied Computing
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A crucial part of a multi-agent system (MAS) design is the specification of agency properties. Traditional approaches to agent systems modeling use diagrams that focus on defining the set of structural and interactive elements such as agents, organizations, actions and messages. Such approaches do not exhibit a proper notation to show agent behavioral properties such as adaptation, mobility and concurrency. The MAS-ML approach to designing agent systems proposed an extension to UML 2.0 to provide a proper notation to model structural and dynamic characteristics of a MAS. In this paper we enhance MAS-ML dynamic diagrams, the extended sequence and activity diagrams, to describe the basic guidelines to model behavioral properties and we show some examples of how these diagrams support the behavioral properties specification, allowing a flexible and easier modeling of agency characteristics.