Agents Swarming in Semantic Spaces to Corroborate Hypotheses

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 provides an overview of an Ant CAFÉ prototype. It describes the system’s architecture, and provides additional detail on the innovative algorithm for evidence assembly. Initial exp...

• Type: Conference
• Year: 2004
• Where: ATAL
• Authors: Peter Weinstein, H. Van Dyke Parunak, Paul Chiusano, Sven Brueckner
• Keywords: Ant CAFÉ, ATAL 2004, Fine-grained Swarming Agents, Multiple Swarming Processes