The art of Prolog: advanced programming techniques
The art of Prolog: advanced programming techniques
Communications of the ACM
From logic programming to Prolog
From logic programming to Prolog
Prolog++: The Power of Object-Oriented and Logic Programming
Prolog++: The Power of Object-Oriented and Logic Programming
The Knowledge Model of Protégé-2000: Combining Interoperability and Flexibility
EKAW '00 Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling and Management
Using JessTab to Integrate Protégé and Jess
IEEE Intelligent Systems
Jess in Action: Java Rule-Based Systems
Jess in Action: Java Rule-Based Systems
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
A mapping system for the integration of OWL-DL ontologies
Proceedings of the first international workshop on Interoperability of heterogeneous information systems
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
The architecture and design of a malleable object-oriented prolog engine
Proceedings of the 2008 ACM symposium on Applied computing
Translating owl and semantic web rules into prolog: Moving toward description logic programs
Theory and Practice of Logic Programming
DR-Prolog: a system for reasoning with rules and ontologies on the semantic web
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Communications of the ACM
Bootstrapping trust evaluations through stereotypes
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A hybrid reasoning mechanism for effective sensor selection for tasks
Engineering Applications of Artificial Intelligence
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Web Ontology Language (OWL) provides means to semantically represent domain knowledge as ontologies. Then, ontological reasoning allows software agents to effectively share and semantically interpret the knowledge. OWL adopts open world semantics and in order to achieve decidability its expressiveness is strictly limited. Therefore, many real-life problems cannot be represented only using ontologies and cannot be solved using just ontological reasoning. On the other hand, traditional reasoning mechanisms for autonomous agents are mostly based on Logic Programming (LP) and closed world assumption. LP provides a very expressive formal language, however it requires domain knowledge to be encoded as a part of logic programs. In this paper, we propose Ontological Logic Programming (OLP), a novel approach that combines logic programming with ontological reasoning. The proposed approach enables the use of ontological terms (i.e., individuals, classes and properties) directly within logic programs. The interpretation of these terms are delegated to an ontology reasoner during the interpretation of the program. Unlike similar approaches, OLP makes use of the full capacity of both the ontological reasoning and logic programming. Using case-studies, we demonstrate the usefulness of OLP in multi-agent settings.