Collaborating Authors

Open Agent Architecture (OAA)

AITopics Original Links

In a distributed agent framework, we conceptualize a dynamic community of agents, where multiple agents contribute services to the community. When external services or information are required by a given agent, instead of calling a known subroutine or asking a specific agent to perform a task, the agent submits a high-level expression describing the needs and attributes of the request to a specialized Facilitator agent. The Facilitator agent will make decisions about which agents are available and capable of handling sub-parts of the request, and will manage all agent interactions required to handle the complex query. Such a distributed agent architecture allows the construction of systems that are more flexible and adaptable than distributed object frameworks. Individual agents can be dynamically added to the community, extending the functionality that the agent community can provide as a whole.

The Latest: Suspect in Shooting ATF Agent Appears in Court

U.S. News

If convicted, he faces up to 20 years in prison. The ATF agent was shot in the face and is expected to make a full recovery.

Border agents help injured Mexican trying to cross into US illegally

FOX News

President of National Border Patrol Council Brandon Judd explains on'Fox & Friends First.'

Generalizing Multi-Agent Path Finding for Heterogeneous Agents

AAAI Conferences

Multi-Agent Path Finding (MAPF) is the problem of finding non-colliding paths for multiple agents. The classical problem assumes that all agents are homogeneous, with a fixed size and behavior. However, in reality agents are heterogeneous, with different sizes and behaviors. In this paper, we generalize MAPF to G-MAPF for the case of heterogeneous agents. We then show how two previous settings of large agents and k-robust agents are special cases of G-MAPF. Finally, we introduce G-CBS, a variant of the Conflict-Based Search (CBS) algorithm for G-MAPF, which does not cause significant extra overhead.

Free agents


For more than half a century, U.S. government officials have considered disaster scenarios, such as the consequences of a nuclear bomb going off in Washington, D.C. Only now, instead of following fixed story lines and predictions assembled ahead of time, they are using computers to play what-if with an entire artificial society: an advanced type of computer simulation called an agent-based model. Today's version of the nuclear attack model includes a digital simulation of every building in the area affected by the bomb, as well as every road, power line, hospital, and even cell tower. The model includes weather data to simulate the fallout plume. And the scenario is peopled with some 730,000 agents.