Using intelligent agents in military simulation or “using agents intelligently”
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Believability through context using "knowledge in the world" to create intelligent characters
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Flying Together: Modelling Air Mission Teams
Applied Intelligence
Thinking Quickly: Agents for Modeling Air Warfare
AI '98 Selected papers from the 11th Australian Joint Conference on Artificial Intelligence on Advanced Topics in Artificial Intelligence
Open Scene Graph A: Introduction, B: Examples and Applications
VR '04 Proceedings of the IEEE Virtual Reality 2004
Two-aircraft formation flight simulation system based on four-tiered architecture
Computers & Mathematics with Applications
Using ego-centered affordances in multi-agent traffic simulation
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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In this paper we describe a multi-agent simulation called the Human Agent Virtual Environment (or HAVE). HAVE is a test bed to explore agent-environment interaction in multi-agent simulation for defence applications. The primary research driver in the development of HAVE is to explore representations of virtual environments in which both humans and agents are situated, perceive these environments and undertake meaningful and appropriate actions. HAVE models and simulates a Close Air Support (CAS) mission which involves fighter or strike aircraft providing support to ground troops through the use of air-to-ground weapons. This provides a realistic and currently extremely relevant domain in which to explore agent-environment interactions. Three important research challenges have been addressed by the work. The first, is the implementation of a multi-modal representation of the virtual environment, having multiple, parallel yet consistent representations of the virtual world that were accessible to, and tailored for the different simulation components. The second is the used of labeled annotations in the virtual world which the agents could easily access and interpret. The third, the use of an appropriate architecture for capturing and representing interaction between agents and the environment they are situated in.