Agents that learn to explain themselves
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Evolution of the GPGP/TÆMS Domain-Independent Coordination Framework
Autonomous Agents and Multi-Agent Systems
Hierarchical planning in BDI agent programming languages: a formal approach
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
2APL: a practical agent programming language
Autonomous Agents and Multi-Agent Systems
An explainable artificial intelligence system for small-unit tactical behavior
IAAI'04 Proceedings of the 16th conference on Innovative applications of artifical intelligence
What does your actor remember? towards characters with a full episodic memory
ICVS'07 Proceedings of the 4th international conference on Virtual storytelling: using virtual reality technologies for storytelling
Managing a non-linear scenario – a narrative evolution
ICVS'05 Proceedings of the Third international conference on Virtual Storytelling: using virtual reality technologies for storytelling
Modeling agents with a theory of mind: Theory--theory versus simulation theory
Web Intelligence and Agent Systems
Hi-index | 0.00 |
Intelligent agents are used to generate the behavior of characters in virtual training systems. To increase trainees' insight in played training sessions, agents can be equipped with capabilities to explain the reasons for their actions. By using an agent programming language in which declarative aspects of an agent's reasoning process are explicitly represented, explanations revealing the underlying motivations for agents' actions can be obtained. In this paper, a methodology for developing self-explaining agents in virtual training systems is proposed, resulting in agents that can explain their actions in terms of beliefs and goals.