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Welcome to APS 3.0 Help File
This Help File teaches you how to use APS modeling tools.

Contents
APS Help is organized into the following chapters:

Chapter 1: The APS Environment
This chapter introduces you to modeling with APS and using the features and capabilities of the APS 3.0 automatic programming system. In this chapter, you'll learn how to:

• Explore the APS modeling environment.
• Generate automatically your first program.
• Evaluate and test an evolved model.
• Apply an evolved model to make predictions or extrapolations.

Chapter 2: Working with Function Finding Tools
This chapter introduces the APS function finding tools and teaches you how to use them to discover complex nonlinear regression models. In this chapter, you'll learn how to:

• Load the input data for the APS function finding algorithm.
• Explore the APS function kit for function finding problems.
• Explore all the available architectures for building mathematical models.
• Explore the best fitness functions for function finding problems.
• Explore all the learning algorithms available for function finding problems.
• Explore essential evolutionary strategies for an efficient learning.

Chapter 3: Working with Classification Tools
This chapter introduces the APS classification tools and teaches you how to use them to discover complex classification models. In this chapter, you'll learn how to:

• Load the input data for the APS classification algorithm.
• Explore the APS function kit for classification problems.
• Explore all the available architectures for building classification models.
• Explore the best fitness functions for classification problems.
• Explore all the learning algorithms available for classification problems.
• Explore essential evolutionary strategies for an efficient learning.

Chapter 4: Working with Time Series Prediction Tools
This chapter introduces the APS time series prediction tools and teaches you how to use them to discover good prediction models. In this chapter, you'll learn how to:

• Load the input data for the APS time series prediction algorithm.
• Explore the APS function kit for time series prediction.
• Explore all the available architectures for making good predictions.
• Explore the best fitness functions for time series prediction problems.
• Explore all the learning algorithms available for time series prediction problems.
• Explore essential evolutionary strategies for an efficient learning.

Chapter 5: The Architectures of APS Learning Algorithms
This chapter describes the architectures of the learning algorithms used by APS 3.0 and teaches you how to explore them so that you can create models that are extremely accurate and robust. In this chapter, you'll learn about:

• The basic concepts and ideas of gene expression programming.
• The manipulation of random numerical constants in gene expression programming.
• The native language of gene expression programming.

Chapter 6: Genetic Operators
This chapter describes the genetic operators of APS and teaches you how to use them to allow the efficient evolution of your models. In this chapter, you'll learn how to:

• Explore the power of mutation.
• Explore the power of inversion.
• Explore the power of transposition.
• Explore the power of recombination.
• Explore special genetic operators for fine-tuning numerical constants.
• Choose the appropriate rate of modification for an efficient evolution.

Chapter 7: Evolution from Existing Models
This chapter describes how to fine tune an existing model using the evolution with seed facilities of APS. In this chapter, you'll learn how to:

• Optimize further an APS evolved model.
• Change an APS evolved model and use it as seed for further evolution.
• Optimize further human-written models using the change seed menu.
• Add a neutral gene for further fine tuning of complex models.

Chapter 8: Choosing the Fitness Function
This chapter describes the built-in fitness functions of APS and teaches you how to use them to allow the efficient evolution of good models. In this chapter, you'll learn how to:

• Explore the fitness functions used in symbolic regression.
• Explore the fitness functions used in time series prediction.
• Explore the fitness functions used in APS classifier systems.
• Choose the appropriate fitness function for an efficient modeling.
• Design your own fitness functions.

Chapter 9: Analyzing APS Models Statistically
This chapter describes the APS built-in facilities for a rapid statistical evaluation of your models. In this chapter, you'll learn how to:

• Evaluate the statistics of your function finding models.
• Evaluate the statistics of your classification models.
• Evaluate the predictive accuracy of your time series models.

Chapter 10: Generating Code Automatically
This chapter describes the built-in grammars of APS and teaches you how to use them to express your models in the programming language of your choice. In this chapter, you'll learn how to:

• Use the APS built-in parser for translating the evolved models into parse trees.
• Use the APS built-in grammars for translating the evolved models into your preferred language.
• Create your own grammars for the automatic translation of APS evolved models.

Chapter 11: Making Predictions with a Model
This chapter introduces the APS scoring engine and teaches you how to apply immediately the evolved models to make predictions or extrapolations. In this chapter, you'll learn how to:

• Score databases.
• Score text files.
• Make predictions with time series models.

Chapter 12: Settings and Features
This chapter gives a brief description of all the settings and features of APS. In this chapter, you can find information about:

• The settings and features for function finding problems.
• The settings and features for classification problems.
• The settings and features for time series prediction problems.

Chapter 13: APS Editions
This chapter describes the four APS editions (Standard, Advanced, Professional, and Academic) and gives specific information about the requirements and installation of each one of them. In this chapter, you can find information about:

• The different editions of APS 3.0.
• The minimum requirements for a successful installation of APS.
• The installation procedure of APS 3.0 in your computer.
• All the menus of APS 3.0.
• The license agreement of APS 3.0.
• The Demo of APS 3.0.

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