Global convergence of local agent behaviors
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Model-guided information discovery for intelligence analysis
Proceedings of the 14th ACM international conference on Information and knowledge management
MLBP: MAS for large-scale biometric pattern recognition
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
MLBP: MAS for large-scale biometric pattern recognition
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Hybrid multi-agent systems: integrating swarming and BDI agents
ESOA'06 Proceedings of the 4th international conference on Engineering self-organising systems
Environments for multiagent systems state-of-the-art and research challenges
E4MAS'04 Proceedings of the First international conference on Environments for Multi-Agent Systems
Analyzing stigmergic learning for self-organizing mobile ad-hoc networks (MANET's)
Engineering Self-Organising Systems
A survey of environments and mechanisms for human-human stigmergy
E4MAS'05 Proceedings of the 2nd international conference on Environments for Multi-Agent Systems
Sift and sort: climbing the semantic pyramid
ESOA'05 Proceedings of the Third international conference on Engineering Self-Organising Systems
| Hi-index | 0.00 |
To anticipate and prevent acts of terrorism, Indications and Warnings analysts try to connect clues gleaned from massive quantities of complex data. Multi-agent approaches to support Indications and Warnings are appropriate because ownership and security issues fragment the data. Furthermore, the massive scale of the data suggests the need for large numbers of agents. The Ant CAFÉ system uses fine-grained swarming agents to extract and organize textual evidence that corroborates hypotheses about the state of the world. Multiple swarming processes are required, including the clustering of paragraphs, identification of semantic relations in text, and assembly of evidence into structures that instantiate the hypothesis. These processes occur in semantic spaces defined using the WordNet ontology. This paper describes an Ant CAFÉ prototype. It describes the systemýs architecture, and provides detail on the innovative algorithm for evidence assembly. Initial experiments using artificially generated data confirm that a global property that we call "clarity" emerges from agent decisions made in a local, and therefore scalable, manner.