Algorithmic Learning Theory

4th International Workshop on Analogical and Inductive Inference, Aii '94, 5th International Workshop on Algorithmic Learning Theory, Alt '94, Reinhardsbrunn Castle, Germany, October 10 - 15, 1994. Proceedings

By: Klaus P. Jantke (Editor), Setsuo Arikawa (Editor)

Write A Review

Paperback | 28 September 1994

At a Glance

Paperback
600 Pages

Dimensions(cm)
23.39 x 15.6 x 3.07

Paperback

$84.99

or 4 interest-free payments of $21.25 with

Ships in 5 to 7 business days

This volume presents the proceedings of the Fourth International Workshop on Analogical and Inductive Inference (AII '94) and the Fifth International Workshop on Algorithmic Learning Theory (ALT '94), held jointly at Reinhardsbrunn Castle, Germany in October 1994. (In future the AII and ALT workshops will be amalgamated and held under the single title of Algorithmic Learning Theory.)
The book contains revised versions of 45 papers on all current aspects of computational learning theory; in particular, algorithmic learning, machine learning, analogical inference, inductive logic, case-based reasoning, and formal language learning are addressed.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $89.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.

Defective items

If there is a problem with any of the items received for your order then the Booktopia Customer Care team is ready to assist you.

For more info please visit our Help Centre.

You Can Find This Book In

Non-Fiction Language & Linguistics Linguistics Philosophy Philosophy & Logic Computing & I.T.Computer Science Artificial Intelligence Expert Systems & Knowledge-Based Systems Mathematics Mathematical Foundation Mathematical Logic

Mathematical Theory of Computation Machine Learning

Towards Efficient Inductive Synthesis from Input/Output Examples	p. 1
Deductive Plan Generation	p. 2
From Specifications to Programs: Induction in the Service of Synthesis	p. 6
Average Case Analysis of Pattern Language Learning Algorithms	p. 8
Enumerable Classes of Total Recursive Functions: Complexity of Inductive Inference	p. 10
Derived Sets and Inductive Inference	p. 26
Therapy Plan Generation as Program Synthesis	p. 40
A Calculus for Logical Clustering	p. 56
Learning with Higher Order Additional Information	p. 64
Efficient Learning of Regular Expressions from Good Examples	p. 76
Identifying Nearly Minimal Godel Numbers from Additional Information	p. 91
Co-Learnability and FIN-Identifiability of Enumerable Classes of Total Recursive Functions	p. 100
On Case-Based Representability and Learnability of Languages	p. 106
Rule-Generating Abduction for Recursive Prolog	p. 121
Fuzzy Analogy Based Reasoning and Classification of Fuzzy Analogies	p. 137
Explanation-Based Reuse of Prolog Programs	p. 149
Constructive Induction for Recursive Programs	p. 161
Training Digraphs	p. 176
Towards Realistic Theories of Learning	p. 187
A Unified Approach to Inductive Logic and Case-Based Reasoning	p. 210
Three Decades of Team Learning	p. 211
On-line Learning with Malicious Noise and the Closure Algorithm	p. 229
Learnability with Restricted Focus of Attention Guarantees Noise-Tolerance	p. 248
Efficient Algorithm for Learning Simple Regular Expressions from Noisy Examples	p. 260
A Note on Learning DNF Formulas Using Equivalence and Incomplete Membership Queries	p. 272
Identifying Regular Languages over Partially-Commutative Monoids	p. 282
Classification Using Information	p. 290
Learning from Examples with Typed Equational Programming	p. 301
Finding Tree Patterns Consistent with Positive and Negative Examples Using Queries	p. 317
Program Synthesis in the Presence of Infinite Number of Inaccuracies	p. 333
On Monotonic Strategies for Learning r.e. Languages	p. 349
Language Learning under Various Types of Constraint Combinations	p. 365
Synthesis Algorithm for Recursive Processes by [mu]-Calculus	p. 379
Monotonicity versus Efficiency for Learning Languages from Texts	p. 395
Learning Concatenations of Locally Testable Languages from Positive Data	p. 407
Language Learning from Good Examples	p. 423
Machine Discovery in the Presence of Incomplete or Ambiguous Data	p. 438
Set-Driven and Rearrangement-Independent Learning of Recursive Languages	p. 453
Refutably Probably Approximately Correct Learning	p. 469
Inductive Inference of an Approximate Concept from Positive Data	p. 484
Efficient Distribution-Free Population Learning of Simple Concepts	p. 500
Constructing Predicate Mappings for Goal-Dependent Abstraction	p. 516
Learning Languages by Collecting Cases and Tuning Parameters	p. 532
Mutual Information Gaining Algorithm and Its Relation to PAC-Learning Algorithm	p. 547
Inductive Inference of Monogenic Pure Context-Free Languages	p. 560
Index of Authors	p. 575
Table of Contents provided by Blackwell. All Rights Reserved.

Algorithmic Learning Theory

4th International Workshop on Analogical and Inductive Inference, Aii '94, 5th International Workshop on Algorithmic Learning Theory, Alt '94, Reinhardsbrunn Castle, Germany, October 10 - 15, 1994. Proceedings

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

More in Mathematical Theory of Computation

Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers

16th International Workshop, STACOM 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Revised Selected Papers

AI Engineering

Building Applications with Foundation Models

Discrete Mathematics for Computing

Grassroots

Swim Training Patterns

1st Edition - Plan your Training Sessions with the Power of Mathematics

Algorithms in C, Parts 1-4

3rd Edition - Fundamentals, Data Structures, Sorting, Searching

Effective Machine Learning Teams

Best Practices for ML Practitioners

Beading With Algorithms

Cellular Automata In Peyote Stitch

Mathematical Foundations of Deep Learning

Theory and Algorithms

Mathematical Foundations of Deep Learning

Theory and Algorithms

Theory of Computation for Software Developers

Nonlinear Analysis for Human Movement Variability

Machine Learning Interviews

Kickstart Your Machine Learning and Data Career

Zhang Time Discretization (ZTD) Formulas and Applications

Decentralized Futures

Navigating the Integration of Blockchain Technology with Artificial Intelligence

Metaheuristic Algorithms

Theory and Practice

Mining Complex Networks

Advances in Applied Mathematics

Mining Complex Networks

Advances in Applied Mathematics

Introduction to Modern Cryptography

Revised Third Edition

Scientific Computing and Software

Go20 CSCS, Ghajnsielem, Malta, May 20-24, 2024

Python Essentials

Symbolic and Numeric Problem-Solving in Engineering

Why Don t Rabbits Rule The World?

Mathematical answers to life s key questions

Linear Algebra with Applications in Machine Learning

From Intuitive Understanding to Python Coding

Guide to Graph Algorithms

Sequential, Parallel and Distributed

Introduction to Numerical Mathematics

Theory, Practice and Numerous Examples

This product is categorised by