concerns an agent dealing with a fire alarm. Achieving the scenario as ... meaning or function (e.g. open door or grab fire extinguisher). This will delegate.
Towards a Design Approach for Integrating BDI Agents in Virtual Environments Joost van Oijen and Frank Dignum University of Utrecht PO Box 80.089, 3508 TB Utrecht, the Netherlands {oijen,dignum}@cs.uu.nl Keywords: Intelligent Virtual Agents, BDI Agents, Virtual Environments.
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Introduction
Employing agent technology for virtual character behavior in games and simulations enforces a distributed IVA design where the agent is part of the cognitive layer, situated in a multi-agent system, and its embodiment makes up the physical layer, situated in a game engine. Creating the mind-body connection is not straightforward since one has to bridge the conceptual gap present between agent and game engine technology. In this paper we present key conceptual design issues that have to be tackled within this connection in order to ensure an IVA’s ability to express certain aspects of natural behavior in real-time.
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Design Issues
Figure 1 shows a small scenario which we’ll use to illustrate the design issues. It concerns an agent dealing with a fire alarm. Achieving the scenario as described, the agent requires high-level decision making as offered by the BDI-paradigm including plan execution, detecting plan failure, adopting new goals based on new situations and recognizing when to stop pursuing goals when they are no longer relevant. Within this small scenario, a few important design issues can be identified which are described below. The first issue concerns the level of abstraction for the agent’s sense and act interface. An agent can reason efficiently in a human-like manner when it is able to sense its environment at a strategic abstraction level based on meaningful concepts (e.g. door or fire). Though, this is generally not the level at which information is represented in a game engine and one is required to bridge the gap in representational levels. A similar issue holds true for acting. An agent can act efficiently when it can perform more high-level actions conveying a specific meaning or function (e.g. open door or grab fire extinguisher ). This will delegate a certain level of control to the game engine and prevents an agent from micromanaging every detail of behavior realization. The second issue concerns real-time perceptual attention which is an important ability for an agent to behave more naturally. Referring to the example H. H¨ ogni Vilhj´ almsson et al. (Eds.): IVA 2011, LNAI 6895, pp. 462–463, 2011. c Springer-Verlag Berlin Heidelberg 2011
Towards Integrating BDI Agents in Virtual Environments
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Fig. 1. Example Scenario
scenario, an agent in search for a fire extinguisher would not need to pay attention to all other types of objects in the room. Receiving too much irrelevant sensory information could slow down its deliberation cycle and may lead to slow reaction times. An agent should have the ability to control the flow of sensory information preventing it from reasoning about irrelevant information on one hand but still let it be susceptible for unexpected changes in the environment on the other hand (e.g. react to a fire alarm). The third issue concerns embodiment control. First of all, an agent should be able to perform multimodal behavior in a visually fluent manner that seems natural for human behavior. This requires a certain level of anticipation on future actions to perform, allowing seamless transitions from one action to the next, preventing unnatural or ’robotic’ movements (e.g. move to door followed by open door ). Further, an agent should be able to interrupt planned or active actions in order to naturally transit to newly dispatched actions (e.g. start searching for a fire extinguisher after noticing the fire). Last, since actions can be designed at a more functional level, the meaning of an action’s success or failure becomes less obvious. Being able to perceive a reason for failure within the context of an action’s execution allows an agent to make intelligent decisions on future actions or plans (e.g. open door failed because it is locked).
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Conclusions
In the scope of a broader effort to develop a structured solution for connecting multi-agent systems to game engines, a middleware framework has been designed for connecting an IVA’s cognitive and physical layer focusing on the previously identified design issues. A more technical overview can be found in [1].
Reference 1. van Oijen, J., Vanh´ee, L., Dignum, F.: CIGA: A Middleware for Intelligent Agents in Virtual Environments. In: Proceedings of the 3rd International Workshop on Agents for Education, Games and Simulations, AAMAS 2011 (2011)
