Artificial intelligence and mathematical theory of computation
Artificial Intelligence
Computational conflicts: conflict modeling for distributed intelligent systems
Computational conflicts: conflict modeling for distributed intelligent systems
ACM Computing Surveys (CSUR)
Multiagent Systems: A Survey from a Machine Learning Perspective
Autonomous Robots
Boosting and Structure Learning in Dynamic Bayesian Networks for Audio-Visual Speaker Detection
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
A retraining methodology for enhancing agent intelligence
Knowledge-Based Systems
Learning communicative actions of conflicting human agents
Journal of Experimental & Theoretical Artificial Intelligence
Ranking semantic information for e-government: complaints management
OBI '08 Proceedings of the first international workshop on Ontology-supported business intelligence
Automatic synthesis of new behaviors from a library of available behaviors
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Ontologies for supporting negotiation in e-commerce
Engineering Applications of Artificial Intelligence
Modelling user preferences and mediating agents in electronic commerce
Knowledge-Based Systems
Using argumentation to model and deploy agent-based B2B applications
Knowledge-Based Systems
Discovering common outcomes of agents' communicative actions in various domains
Knowledge-Based Systems
Concept-based learning of human behavior for customer relationship management
Information Sciences: an International Journal
Assessing plausibility of explanation and meta-explanation in inter-human conflicts
Engineering Applications of Artificial Intelligence
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We develop a generic software component for computing consecutive plausible mental states of human agents. The simulation approach to reasoning about mental world is introduced that is based on exhaustive search through the space of available behaviors. This approach to reasoning is implemented as a logic program in a natural language multiagent mental simulator NL_MAMS, which yields the totality of possible mental states few steps in advance, given an arbitrary initial mental state of participating agents. Due to an extensive vocabulary of formally represented mental attitudes, communicative actions and accumulated library of behaviors, NL_MAMS is capable of yielding much richer set of sequences of mental state than a conventional system of reasoning about beliefs, desires and intentions would deliver. Also, NL_MAMS functions in domain-independent manner, outperforming machine learning-based systems for predicting behaviors of human agents in broad domains where training sets are limited. We evaluate the correctness, coverage and maximum complexity of the NL_MAMS and discuss its integration with other reasoning components and its application domains. The proposed component is intended to be integrated into eBay human behavior simulation system, predicting behavior of buyers and sellers in normal and conflict situations. Also, NL_MAMS can be a part of any software system where modeling of human users is necessary, such as a personalized assistant, a tutoring or decision support system, advisor, recommender and conflict resolver.