1. Introduction

   • John Case
   • Anselm Blumer

   Introduction Pages: 103 - 106

2. Introduction

   • John Case
   • Anselm Blumer

   EditorialNotes Pages: 103 - 106

3. Lower Bound Methods and Separation Results for On-Line Learning Models

   • Wolfgang Maass
   • György Turán

   OriginalPaper Pages: 107 - 145

4. Lower bound methods and separation results for on-line learning models

   • Wolfgang Maass
   • György Turán

   OriginalPaper Pages: 107 - 145

5. Learning Conjunctions of Horn Clauses

   • Dana Angluin
   • Michael Frazier
   • Leonard Pitt

   OriginalPaper Pages: 147 - 164

6. Learning conjunctions of Horn clauses

   • Dana Angluin
   • Michael Frazier
   • Leonard Pitt

   OriginalPaper Pages: 147 - 164

7. A learning criterion for stochastic rules

   • Kenji Yamanishi

   OriginalPaper Pages: 165 - 203

8. A Learning Criterion for Stochastic Rules

   • Kenji Yamanishi

   OriginalPaper Pages: 165 - 203

9. On the Computational Complexity of Approximating Distributions by Probabilistic Automata

   • Naoki Abe
   • Manfred K. Warmuth

   OriginalPaper Pages: 205 - 260

10. On the computational complexity of approximating distributions by probabilistic automata

    • Naoki Abe
    • Manfred K. Warmuth

    OriginalPaper Pages: 205 - 260

11. A Universal Method of Scientific Inquiry

    • Daniel N. Osherson
    • Michael Stob
    • Scott Weinstein

    OriginalPaper Pages: 261 - 271

12. A universal method of scientific inquiry

    • Daniel N. Osherson
    • Michael Stob
    • Scott Weinstein

    OriginalPaper Pages: 261 - 271