Artificial Intelligence
Constructive interpretation of human-generated exceptions during plan execution
Constructive interpretation of human-generated exceptions during plan execution
A collaborative parametric design agent
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Exploiting meta-level information in a distributed scheduling system
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Iterative Development and Validation of a Simulation-Based Medical Tutor
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Causal and Teleological Reasoning In Circuit Recognition
Causal and Teleological Reasoning In Circuit Recognition
CAUSAL REPRESENTATION OF PATIENT ILLNESS FOR ELECTROLYTE AND ACID-BASE DIAGNOSIS
CAUSAL REPRESENTATION OF PATIENT ILLNESS FOR ELECTROLYTE AND ACID-BASE DIAGNOSIS
Increasing coherence in a distributed problem-solving network
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
The persona effect: affective impact of animated pedagogical agents
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Afterword: from this revolution to the next
Smart machines in education
Visual Emotive Communication in Lifelike Pedagogical Agents
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
Realtime generation of customized 3D animated explanations for knowledge-based learning environments
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
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This paper examines the problem of modeling multiple agents within an intelligent simulation-based tutor. Multiple agent and planning technology were used to enable the system to critique a human agent's reasoning about multiple agents. This perspective arises naturally whenever a student must learn to lead and coordinate a team of people. The system dynamically selected teaching goals, instantiated plans and modeled the student and the domain as it monitored the student's progress. The tutor provides one of the first complete integrations of a real-time simulation with knowledge-based reasoning. Other novel techniques of the system are reported, such as common-sense reasoning about plans, reasoning about protocol mechanisms, and using a real-time simulation for training.