| 1 | A theory of predicate invention Akama K. | .... 7 |
| 2 | A theoretical framework for predicate invention Muggleton S. | .... 19 |
| 3 | Inverting implication Muggleton S. | .... 20 |
| 4 | Confirmation theory and machine learning Gillies D. | .... 41 |
| 5 | Towoard inductive generalisation in higher order logic Feng C.,Muggleton S. | .... 53 |
| 6 | Abstraction based analogical reasoning for natural deducation proof Harao M. | .... 64 |
| 7 | Explanation-based generalization by analogical reasoning Hirowatari E.,Arikawa S. | .... 76 |
| 8 | Fundamental Properties of Inductive Reasoning | .... 88 |
| 9 | A personal approach to linguistic oriented Inductive Logic Programming Koch G. | .... 89 |
| 10 | Distinguishing excepttions from noise in non-monotonic learning Srinivasan A.,Muggleton S.,Bain M. | .... 98 |
| 11 | Implementations,Experiments and Applocations | .... 109 |
| 12 | Handling noise in Inductive Logic Programming Dzeroski S.,Bratko I. | .... 110 |
| 13 | Use of heuristics in empirical inductive logic programming Lavrac N.,Cestnik B.,Dzeroski S. | .... 127 |
| 14 | Constraint-directed generalization for learning spatical relations Mizoguchi F.,Ohwada H. | .... 143 |
| 15 | Automated debugging of logic programs via thory revision Mooney R.,Richads B. | .... 161 |
| 16 | Correcting multiple faults in the concept and subconcepts by learning and abduction Tangkitvanich S.,Numao M.,Shimura M. | .... 173 |
| 17 | Learning optimal KRK strategies Bain M. | .... 189 |
| 18 | Drug design by machine learning King R.,Muggleton S.,Lewis R.,Sternberg M. | .... 203 |
| 19 | Protein secondary structure prediction using logic Muggleton S.,King R.,Sterberg M. | .... 229 |
| 20 | Testing the applicability of ILP systems Morales E. | .... 261 |
| 21 | Automatically constructing control systems by observing fman behaviour Sammut C. | .... 272 |
| End | .... 284 |