Neural networks primer, part I
AI Expert
Communications of the ACM
Genetic algorithms and classifier systems: foundations and future directions
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Bucket brigade performance: I. Long sequences of classifiers
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Bucket brigade performance: II. Default hierarchies
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
SIGCSE '88 Proceedings of the nineteenth SIGCSE technical symposium on Computer science education
Introducing parallel processing at the undergraduate level
SIGCSE '88 Proceedings of the nineteenth SIGCSE technical symposium on Computer science education
An undergraduate parallel processing laboratory
SIGCSE '88 Proceedings of the nineteenth SIGCSE technical symposium on Computer science education
Communications of the ACM
Neural computing: theory and practice
Neural computing: theory and practice
Neurocomputing: foundations of research
Neurocomputing: foundations of research
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Neural networks and artificial intelligence
SIGCSE '89 Proceedings of the twentieth SIGCSE technical symposium on Computer science education
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Towards the genetic synthesis of neural network
Proceedings of the third international conference on Genetic algorithms
The appeal of parallel distributed processing
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Learning and relearning in Boltzmann machines
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Parallel distributed processing: explorations in the microstructure, vol. 2: psychological and biological models
Designing application-specific neural networks using the genetic algorithm
Advances in neural information processing systems 2
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Perceptrons: An Introduction to Computational Geometry
Perceptrons: An Introduction to Computational Geometry
A novel approach to teaching artificial intelligence
SIGCSE '95 Proceedings of the twenty-sixth SIGCSE technical symposium on Computer science education
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This paper describes an introductory course on biologically based sub-symbolic machine learning paradigms. Specifically, this paper covers Artificial Neural Networks, Genetic Algorithms and Genetics-Based Machine Learning. It provides the structure, motivation, content, texts and tools for the course. This course is suitable for an upper division undergraduate level course or as an introductory graduate course. The paper includes a section on bibliographical references to aid the instructor in preparing for this course.