AI & Logic Programming
Cellular Automata and Complexity
December 19th, 2007 | posted by adminPart 1: Primary Papers
* Statistical Mechanics of Cellular Automata
* Algebraic Properties of Cellular Automata
* Universality and Complexity in Cellular Automata
* Computation Theory of Cellular Automata
* Undecidability and Intractability in Theoretical Physics
* Two-Dimensional Cellular Automata
* Origins of Randomness in Physical Systems
* Thermodynamics and Hydrodynamics of Cellular Automata
* Random Sequence Generation by Cellular Automata
* Approaches to Complexity Engineering
Building Expert Systems In Prolog
December 19th, 2007 | posted by adminTable of contents
1 Introduction
2 Using Prolog's Inference Engine
3 Backward Chaining with Uncertainty
4 Explanation
5 Production Systems
6 Frames
7 Integration
8 Backward Chaining Indexes
9 User Interface
10 Two Hybrids
11 Prototyping
12 Rubik's Cube
13 Appendix
Artificial Intelligence II
December 19th, 2007 | posted by admin* Artificial Intelligence II - Introduction
* AI Key Concepts - Revisited
* Knowledge Representation
* Logic Knowledge Representation
* Procedural Knowledge Representations
* Weak Slot and Filler Structures
* Strong Slot and Filler Structures
* Reasoning with Uncertainty: Non-Monotonic Reasoning
* Uncertain Reasoning: Statistical Methods
* Distributed Reasoning
* Planning I
* Planning II
* Learning I
* Learning II
* Common Sense
* Vision I
* Vision II
* VISION III
* Vision IV
Artificial Intelligence I
December 19th, 2007 | posted by adminTable of Contents.
1 GENERAL INTRODUCTION; AI DEFINITIONS; A I TECHNIQUES;
SIMPLE GAME , TIC TAC TOE; QUESTION ANSWERING SYSTEMS; ALGORITHMS & DATA STRUCTURES; SAMPLE DIALOGUE SHOPPING; SUCCESS CRITERIA;
2 THE ELEMENTS AND CHARACTERISTICS OF THE LISP
PROGRAMMING LANGUAGE USING COMMON LISP ON MACS;
3 USER DEFINED FUNCTIONS IN LISP
Artificial Intelligence and Responsive Optimization, 2nd edition,
December 19th, 2007 | posted by adminThe purpose of this book is to apply the Artificial Intelligence and control systems to different real models.
In part 1, we have defined a fuzzy utility system, with different financial goals,
different levels of risk tolerance and different personal preferences, liquid assets, etc. A fuzzy system (extendible to a neutrosophic system) has been designed for the evaluations of the financial objectives. We have investigated the notion of fuzzy and neutrosophiness with respect to time management of money.
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