Distributed artificial intelligence testbeds
Foundations of distributed artificial intelligence
T&Aelig;MS: a framework for environment centered analysis and design of coordination mechanisms
Foundations of distributed artificial intelligence
Constructing and dynamically maintaining perspective-based agent models in a multi-agent environment
Proceedings of the third annual conference on Autonomous Agents
Agent Communication Languages: The Current Landscape
IEEE Intelligent Systems
Domain independent conflict resolution for dynamically organized multi-agent systems
Domain independent conflict resolution for dynamically organized multi-agent systems
Belief Revision Process Based on Trust: Agents Evaluating Reputation of Information Sources
Proceedings of the workshop on Deception, Fraud, and Trust in Agent Societies held during the Autonomous Agents Conference: Trust in Cyber-societies, Integrating the Human and Artificial Perspectives
Sensible agent technology improving coordination and communication in biosurveillance domains
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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Sensible Agents have been engineered to solve distributed problems in complex, uncertain, and dynamic domains. Each Sensible Agent is composed of four modules: the Action Planner, Perspective Modeler, Conflict Resolution Advisor, and Autonomy Reasoner. These modules give Sensible Agents the abilities to plan, model, resolve individual conflicts, and change agent system organization. Two component suites provide a variety of user- oriented features: the Sensible Agent Run- time Environment (SARTE) and the Sensible Agent Testbed. The SARTE provides facilities for instantiating Sensible Agents, deploying a Sensible Agent system, and monitoring run- time operations. The Sensible Agents Testbed facilitates automated generation of parameter combinations for controlled experiments, deterministic and non-deterministic simulation, and configuration of Sensible Agents and data acquisition. Experimentation is a crucial step in gaining insight into the behavior of agents, as well as evidence toward or against hypotheses. Using a real- world example, this paper explains and demonstrates: (1) the functional capabilities of Sensible Agents, (2) the Sensible Agent Run- Time Environments facilities for monitoring and control of Sensible Agent systems and (3) the experimental set- up, monitoring, and analysis capabilities of the Sensible Agent Testbed.