SOAR: an architecture for general intelligence
Artificial Intelligence
Adaptive action selection for cooperative agent teams
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
The imperative future: principles of executable temporal logic
The imperative future: principles of executable temporal logic
Modelling social action for AI agents
Artificial Intelligence - Special issue: artificial intelligence 40 years later
It knows what you're going to do: adding anticipation to a Quakebot
Proceedings of the fifth international conference on Autonomous agents
An architecture for Real-Time Reasoning and System Control
IEEE Expert: Intelligent Systems and Their Applications
BDI-Based Development of Virtual Characters with a Theory of Mind
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Modeling Agents with a Theory of Mind
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
PsychSim: modeling theory of mind with decision-theoretic agents
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Evaluation of virtual agents utilizing theory of mind in a real time action game
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Moving Target Search Using Theory of Mind
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
An intelligent agent model with awareness of workflow progress
Applied Intelligence
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When developing intelligent agents, approaches that allow the anticipation of other agents is of utmost importance. For humans, this has also been shown to be crucial to establish good interactions. In this paper, a design for an agent that is equipped with theory of mind based reasoning capabilities is presented. The approach moves beyond the state of the art from several angles: first, it allows for the expression of certainties with respect to the predicted states of the other agents. Second, it allows the prediction during a substantial number of time steps in the future, thereby utilizing the theory of mind model multiple times. The approach has been applied to the domain of fighter pilots whereby intelligent opponents are developed to facilitate dedicated training for F16 fighter pilots.