Hypothesis Testing

The principal investigator in this project was Paul Compton. The aim was to build tools to assist medical researchers in building and maintaining hypotheses that explain their experimental results. The project involved aspects of belief revision and machine learning. Ashesh Mahidadia used ILP methods to learn qualitative models.


Mahidadia, A., Sammut, C. and Compton, P. (1992). Inventing Causal Qualitative Models: A Tool for Experimental Research. In A. Adams & L. Sterling (Eds) Proceedings of the Fifth Australian Conference on Artificial Intelligence, Hobart: World Scientific, pp. 317-322.

Mahidadia, A., Sammut, C. and Compton, P. (1992). Buidling and Maintaing Causal Theories. Proceedings of the AAAI Symposium on Knowledge Assimilation, Stanford, pp. 97-103.

Mahidadia, A., Sammut, C. and Compton, P. (1994). Applying Inductive Logic Programming to Causal Qualitative Models in Neuroendocrinology. In C. Zhang, J. Debenham, & D. Lukose (Eds.), Artificial Intelligence: Sowing the Seeds of the Future. (pp. 68-75). Armidale: World Scientific Publishers.

Mahidadia, A., Sammut, C., and P.Compton (1994). Unfolding Learning. In 10th Logic Programming Workshop, Zurich.

Mahidadia, A., Compton, P. and Sammut, C. (1994). Helping Researchers To Construct Scientific Models: A Tool From Inductive Logic Programming. In 4th Japanese Knowledge Acquisition for Knowledge-Based Systems Workshop, Tokyo.