Multi-agent systems (MASs) provide powerful models for representing both real-world systems and applications with an appropriate degree of complexity and dynamics. Several research and industrial experiences have already shown that the use of MASs offers advantages in a wide range of application domains (e.g. financial, economic, social, logistic, chemical, engineering). When MASs represent software applications to be effectively delivered, they need to be validated and evaluated before their deployment and execution, thus methodologies that support validation and evaluation through simulation of the MAS under development are highly required. In other emerging areas (e.g. ACE, ACF), MASs are designed for representing systems at different levels of complexity through the use of autonomous, goal-driven and interacting entities organized into societies which exhibit emergent properties The agent-based model of a system can then be executed to simulate the behavior of the comple!
te system so that knowledge of the behaviors of the entities (micro-level) produce an understanding of the overall outcome at the system-level (macro-level). In both cases (MASs as software applications and MASs as models for the analysis of complex systems), simulation plays a crucial role that needs to be further investigated.

MAS&S 2013 aims at providing a forum for discussing recent advances in Engineering Complex Systems by exploiting Agent-Based Modeling and Simulation. 

• Agent-based simulation techniques and methodologies
• Discrete-event simulation of Multi-Agent Systems
• Simulation as validation tool for the development process of MAS
• Agent-oriented methodologies incorporating simulation tools
• MAS simulation driven by formal models
• MAS simulation toolkits and frameworks
• Testing vs. simulation of MAS
• Industrial case studies based on MAS and simulation/testing
• Agent-based Modeling and Simulation (ABMS)
• Agent Computational Economics (ACE)
• Agent Computational Finance (ACF)
• Agent-based simulation of networked systems
• Scalability in agent-based simulation