A template-based and pattern-driven approach to situation awareness and assessment in virtual humans
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Situation Awareness in Intelligent Agents: Foundations for a Theory of Proactive Agent Behavior
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Modelling situations in intelligent agents
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology)
Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology)
A periphery of Pogamut: from bots to agents and back again
Agents for games and simulations II
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Virtual worlds are inherently complex, dynamic and unpredictable in nature. The interface they provide to external agent systems consists of low-level events and primitive data. This introduces an information representation gap between virtual worlds and declarative BDI-based agent systems. As a result, BDI-based intelligent virtual agents (IVAs) are not capable of identifying the complex abstract situations unfolding in their surrounding environment. In this paper, we describe a two-step process that enables an IVA to identify the complex situations they encounter. First, complex event recognition mechanisms are applied on the low-level sensor data received by an IVA. Complex events identified in the first step are compared against a domain-specific situation model to identify active situations. The situation model helps the agent to be aware of the start and end of situations, and also to be aware of any active situation at any given time.