1. ALT 1990: Tokyo, Japan

Setsuo Arikawa, S. Goto, Setsuo Ohsuga, Takashi Yokomori (Eds.): Algorithmic Learning Theory, First International Workshop, ALT '90, Tokyo, Japan, October 8-10, 1990, Proceedings. Springer/Ohmsha, 1990, ISBN 3-540-19661-7

Invited Papers

Shun-ichi Amari: Mathematical Theory of Neural Learning. 3-20
David Haussler: Decision Theoretic Generalizations of the PAC Learning Model. 21-41
Stephen Muggleton: Inductive Logic Programming. 42-62

Neural Networks

Akira Namatame: Structured Neural Networks and Their Flash Learning. 67-80
Ryuichi Oka: A Self-Organizing Network Composed of Symbol Nodes With Location Parameter. 81-94

Concept Formation and Recognition

B. Shekar, M. Narasimha Murty, G. Krishna: The Function-Acquisition Paradigm in a Knowledge-Based Concept-Synthesis Environment. 97-108
Vladimir D. Gusev, Nadia A. Chuzhanova: The Algorithms of Recognition of the Functional Sites in Genetic Texts. 109-119
Tatsuo Unemi: On Inductive Learning for Three Kinds of Data Structures. 120-133
Ryohei Orihara, Akihiko Osuga, Yoichi Kusui: On Paraphrasing-Based Analogical Reasoning. 134-148

Analogical Reasoning

Masateru Harao: Analogical Reasoning Based on Higher-Order Unification. 151-163
Jun Arima: Analog by Simulation - A Weak Justification Method (Preliminary Report). 164-173
Bipin Indurkhya: On the Role of Interpretive Analogy in Learning. 174-189

Approximate Learning

Yasubumi Sakakibara: Occam Algorithms for Learning From Noisy Examples. 193-208
Jyrki Kivinen: Reliable and Useful Learning with Uniform Probability Distributions. 209-222
Naoki Abe: Learning Commutative Deterministic Finite State Automata in Polynomial Time. 223-235
Nicolò Cesa-Bianchi: Learning the Distribution in the Extended PAC Model. 236-246
Ayumi Shinohara, Satoru Miyano: Teachability in Computational Learning. 247-255
Mark A. Fulk, Sanjay Jain: Approximate Inference and Scientific Method. 256-265

Inductive Inference

Klaus P. Jantke: Monotonic and Non-Monotonic Inductive Inference. 269-281
John Case, Sanjay Jain, Arun Sharma: Anomalous Learning Helps Succinctness (Extended Abstract). 282-288
Steffen Lange, Rolf Wiehagen: Polynomial-Time Inference of Pattern Languages. 289-301
Yuji Takada: Learning Equal Matrix Grammers and Multitape Automata with Structural Information. 302-313
Yuji Takada, Kunihiko Hiraishi, Yasubumi Sakakibara: Exact Learning of Semilinear Sets. 314-324
Pedro Garcia, Enrique Vidal, José Oncina: Learning Locally Testable Languages in the Strict Sense. 325-338
Takeshi Shinohara: Inductive Inference of Monotonic Formal Systems from Positive Data. 339-351

New Learning Paradigms

Shuling Liu, Masami Hagiya: Model Inference of Constrained Recursive Figures. 355-367
Stephen Muggleton, Cao Feng: Efficient Induction of Logic Programs. 368-381
Toshikazu Tanaka: Deciding What to Learn in Explanation-Based Macro-Rule Learning. 382-395
Masami Hagiya: Synthesis of Rewrite Programs by Higher-Order and Semantic Unification. 396-410
Atsushi Togashi, Shoichi Noguchi: Inductive Inference of Term Rewriting Systems Realizing Algebras. 411-424
Philip D. Laird, Evan Gamble: EBG and Term-Rewriting Systems. 425-440

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