MacGyver Virtual Agents: Using Ontologies and
Hierarchies for Resourceful Virtual Human Decision-Making
John T. Balint and Jan M. Allbeck
Extended Abstract. Proceedings of Autonomous Agents and Multi-Agent
Systems, 2013, pages 1153-1154.
Abstract
Virtual Humans are becoming an ever more important asset in games, movies, and training simulations. The ability for virtual
humans to select appropriate actions and objects for plausible
behaviors is vital to creating believable and resourceful agents.
For this purpose, a decision making methodology using
hierarchies of ontologies for both actions and objects is presented.
Objects are given semantic information such as affordances and
physical properties. Affordance theory is applied to determine
viable candidate objects for behaviors, and agents learn which
objects are better choices than others.
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