Personality-rich believable agents that use language
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Bayesian Models for Keyhole Plan Recognition in an Adventure Game
User Modeling and User-Adapted Interaction
Techniques for Plan Recognition
User Modeling and User-Adapted Interaction
Old tricks, new dogs: ethology and interactive creatures
Old tricks, new dogs: ethology and interactive creatures
Better Game Characters by Design: A Psychological Approach (The Morgan Kaufmann Series in Interactive 3D Technology)
Using anticipation to create believable behaviour
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Affordance-Based intention recognition in virtual spatial environments
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
Politeness improves interactivity in dense crowds
Computer Animation and Virtual Worlds
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Autonomous virtual agents generally lack the support to understand a fundamental character in their world --- the user's avatar. This has a negative impact on their behavioural believability. In this paper, we present an approach to detect the intent underlying certain actions of the user. We begin by introducing the relation between intention and action, then proceed on elaborating a framework that can interpret the intent of an action based on the matching and mismatching of anticipated behaviour. We then present a test-case in which our framework is used to create an agent architecture controlling a virtual dog that interacts with the user within a virtual world. Finally, we discuss three aspects of our evaluation: the user's intent recognition, its interpretation and the solution's efficiency. Our results suggest that our solution can be used to detect certain intents and, in such cases, perform similarly to a human observer, with no impact on computational performance.