Dr Chris Ewin
- Artificial Intelligence
Chris Ewin completed his PhD at the University of Melbourne. His thesis explores how AI agents can more efficiently reason about their environment and the effects of their actions. It develops new techniques for reasoning about the performance of expressive software agents in complex, long-lived environments. He is currently an Associate Lecturer at the University of Melbourne. His research interests include knowledge representation, artificial intelligence and multi-agent systems.
- Ewin, C. Optimizing projection in the situation calculus. . 2018.
- Ewin, C.; Pearce, A.; Vassos, S. Optimizing Long-Running Action Histories in the Situation Calculus Through Search. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2015, Vol. LNCS 9387, pp. 85-100. DOI: 10.1007/978-3-319-25524-8_6
- Ewin, C.; Pearce, A.; Vassos, S. Transforming Situation Calculus Action Theories for Optimised Reasoning. Proceedings of the Fourteenth International Conference on Principles of Knowledge Representation and Reasoning. AAAI Press. 2014, pp. 448-457.