Track Description
The purpose of ADS session is to facilitate
dissemination of the most recent advancements in the theory, methodology, application, and
toolkits of agent-directed simulation which considers full synergy of simulation and agents. ADS
is comprehensive in the integration of simulation and agents, by including models that use
agents to develop domain-specific simulations and by also including the use of agent technology
to develop simulation techniques and toolkits that are subsequently applied, either with or
without agents.
Agent-directed simulation consists of three distinct, yet related areas that can be grouped under
two categories as follows:
- Contribution of Simulation to Agents (agent simulation):
Simulation of agent-based systems in science, engineering, human and social dynamics, military applications etc.
- Contribution of Agents to Simulation (which consists of two group activities):
- Agent-supported simulation which deals with the use of agents as a support facility (in front-end as well as back-end user-system interfaces) to enable computer assistance in problem solving or enhancing cognitive capabilities of modeling and simulation system (such as understanding and learning abilities);
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Agent-monitored simulation which focuses on the use of agents for the run time activities including the generation of model behavior, agent-triggered simulation and monitoring simulation models and/or experimental conditions during run-time. Agent-monitored simulation includes monitoring dynamic couplings by changing some component models in the coupling and/or by changing their input/output relationships.
Topics list:
Technical and position papers are solicited on the theory, methodology, technology, tools, toolkits, and environments as well as applications. Topics include, but are not limited to the following areas:
- Theory/Methodology:
- High-level agent specification languages for modeling and simulation.
- Agent
programming and simulation modeling languages.
- Agent programming and simulation modeling languages.
- Distributed simulation for multi-agent systems.
- Formal models of agents and agent societies.
- Advanced agent features for agent simulation.
- Cooperation modeling with holonic agents.
- Agent with personality, agents with dynamic personality, agent with emotions, agents having different types of intelligence such as emotional intelligence, agents with several types of understanding abilities such as multi-vision understanding ability, trustworthy agents, moral agents.
- Verification, validation, and testing of agent-directed simulations.
- Assurance of ethical behavior in agent-based models.
- Detection of unethical behavior of other agent-based models.
- Technology, tools, toolkits, and environments:
- Agent infrastructures and supporting technologies (e.g., interoperability, agent-oriented software engineering environments).
- Modeling, design, and simulation of agent systems based on service-oriented technologies, pervasive computing, web-services, grid computing, autonomic computing, ambient intelligence.
- Agent architectures, platforms, and frameworks.
- Standard APIs for agent simulation programming.
- Applications:
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Simulation modeling of agent technologies at the organization, interaction (e.g., communication, negotiation, coordination, collaboration) and agent level (e.g., deliberation, social agents, computational autonomy).
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Application of agent simulations in various areas such as biology, business, commerce, economy, engineering, environment, individual, group, and organization behavior, management, simulation gaming/training, science, and social systems.