Embodied agents for multi-party dialogue in immersive virtual worlds
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Where to Look? Automating Attending Behaviors of Virtual Human Characters
Autonomous Agents and Multi-Agent Systems
Toward Alignment with a Virtual Human - Achieving Joint Attention
KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
Formalizing joint attention in cooperative interaction with a virtual human
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Scalable Perception for BDI-Agents Embodied in Virtual Environments
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
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In this paper, we present a computational model of dynamic perceptual attention for virtual humans. The computational models of perceptual attention that we surveyed fell into one of two camps: top-down and bottom-up. Biologically inspired computational models [2] typically focus on the bottom-up aspects of attention, while most virtual humans [1,3,7] implement a top-down form of attention. Bottom-up attention models only consider the sensory information without taking into consideration the saliency based on tasks or goals. As a result, the outcome of a purely bottom-up model will not consistently match the behavior of real humans in certain situations. Modeling perceptual attention as a purely top-down process, however, is also not sufficient for implementing a virtual human. A purely top-down model does not take into account the fact that virtual humans need to react to perceptual stimuli vying for attention. Top-down systems typically handle this in an ad hoc manner by encoding special rules to catch certain conditions in the environment. The problem with this approach is that it does not provide a principled way of integrating the ever-present bottom-up perceptual stimuli with top-down control of attention. This model extends the prior model [7] with perceptual resolution based on psychological theories of human perception [4]. This model allows virtual humans to dynamically interact with objects and other individuals, balancing the demands of goal-directed behavior with those of attending to novel stimuli. This model has been implemented and tested with the MRE Project [5].