contents of artificial intelligencePosted by: | Posted on: November 27, 2020
For more details click on the below link. All Right Reserved. comment that Artificial Intelligence is an effort to create systems that can learn, think, perceive, analyze and act in the same manner as real humans. Here we aim at providing you with all the useful and needful content of engineering as well as career guidance throughout. (KOE038) , CRO, Syllabus: MANUFACTURING PROCESSES (KME-403), Syllabus: ENGINEERING MECHANICS (KME-402). Artificial Intelligence These notes and slides are provided by Mr Anuj Khanna (Asst. Introduction : Introduction to Artificial Intelligence, Foundations and History of Artificial Intelligence, Applications of Artificial Intelligence, Intelligent Agents, Structure of Intelligent Agents. Artificial Intelligence is widely employed by financial institutions and banking institutions to organize and manage data. People have also looked into understanding the phenomena of Artificial Please provide the notes for all the other units as well. Subject:- Artificial Intelligence (NCS702).. Unit-I Many publishers use artificial intelligence to generate their content, for example, The Press Association creates about 30,000 local stories through artificial intelligence. Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Introducing you the topics of Artificial Intelligence (UNIT-I) in very summarized way. Area of Interest- compiler Content of Artificial Intelligence (NCS702),CS 4th Year - UPTU Notes When we take a picture, the artificial intelligence algorithm identifies and detects the person’s face and tags the individuals when we are posting our photographs on social media sites. These notes... UPTUNotes.com is a mission-driven not-for-profit website, a hub which will help you throughout your engineering career, that connects students to college success and opportunities. ... 1 1.1.1 Acting humanly: The Turing test approach ... 2 Artificial intelligence has transformed the content-writing industry because most things are done by artificial intelligence when writing content today. Haptics: The science of touch in Artificial Intelligence (AI). Computer vision, Natural Language Possessing. Area of Interest– compiler design, software engineering & testing, artificial intelligence, image processing, automata theory. Professor, KGI , Kanpur). Artificial intelligence (AI) is the transformative technology of our time. The Notes you have provided are really very helpful, but all the units are nor there. Save my name, email, and website in this browser for the next time I comment. Contents In this Table of Contents, you learn about what Artificial Intelligence contains in detail. I Representations and Methods 1 The Intelligent Computer. Unit-II Pros and Cons of Artificial Intelligence 2020 (Top 20) Currently, artificial intelligence is one of the hottest topics, in the real world and on the internet. Content of Artificial Intelligence (NCS702),CS 4th Year, compiler design, software engineering & testing, artificial intelligence, image processing, automata theory, ELECTRONICS AND COMMUNICATION ENGINEERING NOTES, ELECTRICAL AND ELECTRONICS ENGINEERING NOTES, ELECTRONICS AND COMMUNICATION ENGINEERING PAPER, ELECTRICAL AND ELECTRONICS ENGINEERING PAPER, Click Here To Download Slides of Unit-1 – Part-1, Click Here To Download Slides of Unit-1 – Part-2, AKTU Notes: Artificial Intelligence(NCS702), CS 4th Yr, UNIT 3, Notes: Wireless & Mobile Communication (NEC-801), Unit-II, AKTU Notes: Electronics Engg. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. @2019 - www.uptunotes.com. Professor, KGI , Kanpur). (REC101), Unit-1 (Theory), AKTU Notes: Electronics Engg. AKTU Notes: Artificial Intelligence(NCS702), CS 4th Yr, UNIT... AKTU Notes: Professional Communication , Unit-I [ RAS104... Notes: LASER SYSTEMS AND APPLICATIONS (NOE-033/043), AKTU/UPTU CYBER SECURITY (RHU001A) Previous Year Question Paper, Textile Group / Carpet & Textile Technology. The Field and the Book This Book Has Three Parts The Long-Term Applications Stagger the Imagination The … Part I: Artificial Intelligence Chapter 1 Introduction ... 1 What Is AI? The Long-Term Applications Stagger the Imagination, The Near-Term Applications Involve New Opportunities, Artificial Intelligence Sheds New Light on Traditional Questions, Artificial Intelligence Helps Us to Become More Intelligent, Intelligent Systems Can Help Experts to Solve Difficult Analysis Problems, Intelligent Systems Can Help Experts to Design New Devices, Intelligent Systems Can Learn from Examples, Intelligent Systems Can Provide Answers to English Questions Using both Structured Data and Free Text, Artificial Intelligence Is Becoming Less Conspicuous, yet More Essential, Good Representations Are the Key to Good Problem Solving, Good Representations Support Explicit, Constraint-Exposing Description, A Representation Has Four Fundamental Parts, There Are Many Schools of Thought About the Meaning of Semantics, Theoretical Equivalence Is Different from Practical Equivalence, Feature-Based Object Identification Illustrates Describe and Match, The Describe-and-Match Method and Analogy Problems, Geometric Analogy Rules Describe Object Relations and Object Transformations, Good Representation Supports Good Performance, The Describe-and-Match Method and Recognition of Abstractions, Story Plots Can Be Viewed as Combinations of Mental States and Events, Abstraction Units Enable Question Answering, Problem Solving and Understanding Knowledge, Generate-and-Test Systems Often Do Identification, Good Generators Are Complete, Nonredundant, and Informed, The Key Idea in Means-Ends Analysis Is to Reduce Differences, Difference-Procedure Tables Often Determine the Means, Moving Blocks Illustrates Problem Reduction, The Key Idea in Problem Reduction Is to Explore a Goal Tree, Goal Trees Can Make Procedure Interaction Transparent, Goal Trees Enable Introspective Question Answering, Problem Reduction Is Ubiquitous in Programming, Problem-Solving Methods Often Work Together, Mathematics Toolkits Use Problem Reduction to Solve Calculus Problems, Depth-First Search Dives into the Search Tree, Breadth-First Search Pushes Uniformly into the Search Tree, Nondeterministic Search Moves Randomly into the Search Tree, Quality Measurements Turn Depth-First Search into Hill Climbing, Foothills, Plateaus, and Ridges Make Hills Hard to Climb, Beam Search Expands Several Partial Paths and Purges the Rest, Best-First Search Expands the Best Partial Path, Search Alternatives Form a Procedure Family, The British Museum Procedure Looks Everywhere, Branch-and-Bound Search Expands the Least-Cost Partial Path, Adding Underestimates Improves Efficiency, Redundant Partial Paths Should Be Discarded, Underestimates and Dynamic Programming Improve Branch-and-Bound Search, Several Search Procedures Find the Optimal Path, The Minimax Procedure Is a Lookahead Procedure, The Alpha-Beta Procedure Prunes Game Trees, Alpha-Beta May Not Prune Many Branches from the Tree, Progressive Deepening Keeps Computing Within Time Bounds, Heuristic Continuation Fights the Horizon Effect, Many Rule-Based Systems Are Deduction Systems, A Toy Deduction System Identifies Animals, Rule-Based Systems Use a Working Memory and a Rule Base, Deduction Systems May Run Either Forward or Backward, The Problem Determines Whether Chaining Should Be Forward or Backward, Mycin Diagnoses Bacterial Infections of the Blood, Reaction Systems Require Conflict Resolution Strategies, Procedures for Forward and Backward Chaining, Depth-First Search Can Supply Compatible Bindings for Forward Chaining, Depth-First Search Can Supply Compatible Bindings for Backward Chaining, Relational Operations Support Forward Chaining, The Rete Approach Deploys Relational Operations Incrementally, Reasoning Systems Can Exhibit Variable Reasoning Styles, Probability Modules Help You to Determine Answer Reliability, Two Key Heuristics Enable Knowledge Engineers to Acquire Knowledge, Acquisition Modules Assist Knowledge Transfer, Rule-Based Systems Can Behave Like Idiot Savants, Rule-Based Systems Viewed as Models for Human Problem Solving, Rule-Based Systems Can Model Some Human Problem Solving, Protocol Analysis Produces Production-System Conjectures, SOAR Uses an Automatic Preference Analyzer, Inheritance Enables When-Constructed Procedures to Move Default Slot Values from Classes to Instances, A Class Should Appear Before All Its Superclasses, A Class's Direct Superclasses Should Appear in Order, The Topological-Sorting Procedure Keeps Classes in Proper Order, When-Requested Procedures Override Slot Values, When-Read and When-Written Procedures Can Maintain Constraints, With-Respect-to Procedures Deal with Perspectives and Contexts, Inheritance and Demons Introduce Procedural Semantics, Object-Oriented Programming Focuses on Shared Knowledge, Digesting News Seems to Involve Frame Retrieving and Slot Filling, Event-Describing Frames Make Stereotyped Information Explicit, An Object's Thematic Role Specifies the Object's Relation to an Action, Filled Thematic Roles Help You to Answer Questions, Various Constraints Establish Thematic Roles, A Variety of Constraints Help Establish Verb Meanings, Examples Using Take Illustrate How Constraints Interact, Primitive Actions Describe Many Higher-Level Actions, Actions Often Imply Implicit State Changes and Cause-Effect Relations, Primitive-Action Frames and State-Change Frames Facilitate Question Answering and Paraphrase Recognition, Thematic-Role Frames and Primitive-Action Frames Have Complementary Foci, Propagation of Numbers Through Numeric Constraint Nets, Numeric Constraint Boxes Propagate Numbers through Equations, Propagation of Probability Bounds Through Opinion Nets, Spreadsheets Propagate Numeric Constraints Through Numeric-Constraint Nets, Propagation Moves Probability Bounds Closer Together, Propagation of Surface Altitudes Through Arrays, Local Constraints Arbitrate between Smoothness Expectations and Actual Data, Constraint Propagation Achieves Global Consistency through Local Computation, GENINFER Helps Counselors to Provide Precise Genetic Advice, Propagation of Line Labels through Drawing Junctions, There Are Only Four Ways to Label a Line in the Three-Faced-Vertex World, There Are Only 18 Ways to Label a Three-Faced Junction, Finding Correct Labels Is Part of Line-Drawing Analysis, Waltz's Procedure Propagates Label Constraints through Junctions, Many Line and Junction Labels Are Needed to Handle Shadows and Cracks, Illumination Increases Label Count and Tightens Constraint, The Computation Required Is Proportional to Drawing Size, There Are 13 Ways to Label a Link between Interval Nodes Yielding 169 Constraints, Time Constraints Can Propagate across Long Distances, A Complete Time Analysis Is Computationally Expensive, Quantifiers Determine When Expressions Are True, Interpretations Tie Logic Symbols to Worlds, Using Resolution Requires Axioms to Be in Clause Form, Theorem Proving Is Suitable for Certain Problems, but Not for All Problems, Chronological and Dependency-Directed Backtracking, Nonchronological Backtracking Exploits Dependencies, Truth Propagation Can Establish Justifications, Justification Links Enable Programs to Change Their Minds, Operators Specify Add Lists and Delete Lists, You Can Plan by Searching for a Satisfactory Sequence of Operators, Partial Instantiation Can Help Reduce Effort Too, Finding Operator Sequences Requires Situation Variables, Responding to Near Misses Improves Models, Near-Miss Heuristics Specialize; Example Heuristics Generalize, Learning Usually Must Be Done in Small Steps, Must Links and Must-Not Links Dominate Matching, Models May Be Arranged in Lists or in Nets, Learning about Why People Act the Way they Do, Reification and the Vocabulary of Thematic-Role Frames Capture Sentence-Level Meaning, Explanation Transfer Solves Problems Using Analogy, Commonsense Problem Solving Can Generate Rulelike Principles, The Macbeth Procedure Illustrates the Explanation Principle, The Macbeth Procedure Can Use Causal Chains to Establish Common Context, Explanation-Based Learning Offers More than Speedup, Stupid Matchers Are Slow and Easy to Fool, Matching Inexact Situations Reduces to Backward Chaining, Matching Sheds Light on Analogical Problem Solving, Near-Miss Groups Isolate Suspicious Relations, Suspicious Relation Types Determine Overall Repair Strategy, The Solution May Be to Explain the True-Success Suspicious Relations, Incorporating True-Success Suspicious Relations May Require Search, The Solution May Be to Explain the False-Success Suspicious Relations, Creating a Censor, Failure Can Stimulate a Search for More Detailed Descriptions, The Consistency Heuristic Enables Remembered Cases to Supply Properties, The Consistency Heuristic Solves a Difficult Dynamics Problem, A Fast Serial Procedure Finds the Nearest Neighbor in Logarithmic Time, Parallel Hardware Finds Nearest Neighbors Even Faster, Version Space Consists of Overly General and Overly Specific Models, Generalization and Specialization Leads to Version-Space Convergence, The Version-Space Procedure Handles Positive and Negative Examples Symmetrically, The Version-Space Procedure Enables Early Recognition, Information Theory Supplies a Disorder Formula, Unnecessary Rule Antecedents Should Be Eliminated, Fisher's Exact Test Brings Rule Correction in Line with Statistical Theory, Real Neurons Consist of Synapses, Dendrites, Axons, and Cell Bodies, Simulated Neurons Consist of Multipliers, Adders, and Thresholds, Feed-Forward Nets Can Be Viewed as Arithmetic Constraint Nets, Feed-Forward Nets Can Recognize Regularity in Data, The Back-Propagation Procedure Does Hill Climbing by Gradient Ascent, Gradient Ascent Requires a Smooth Threshold Function, Back Propagation Can Be Understood Heuristically, Back-Propagation Follows from Gradient Descent and the Chain Rule, The Back-Propagation Procedure Is Straightforward, Training May Require Thousands of Back Propagations, Back Propagation Can Get Stuck or Become Unstable, Back Propagation Can Train a Net to Learn to Recognize Multiple Concepts Simultaneously, Perceptrons Have Logic Boxes and Stair-Step Thresholds, The Perceptron Convergence Procedure Guarantees Success Whenever Success Is Possible, Ordinary Algebra Is Adequate to Demonstrate Convergence When There Are Two Weights, Vector Algebra Helps You to Demonstrate Convergence When There Are Many Weights, A Straight-Through Perceptron Can Learn to Identify Digits, The Perceptron Convergence Procedure Is Amazing, There Are Simple Tasks That Perceptrons Cannot Do, Gaussian Functions Centered on Samples Enable Good Interpolations, Given Sufficient Nodes, Nets Can Interpolate Perfectly, Given Relatively Few Nodes, Approximation Nets Can Yield Approximate Results for All Sample Inputs, Too Many Samples Leads to Weight Training, Overlooked Dimensions May Explain Strange Data Better than Elaborate Approximation, The Interpolation-Approximation Point of View Helps You to Answer Difficult Design Questions, Gaussian Functions Can Be Computed as Products of Gaussian Functions, Genetic Algorithms Involve Myriad Analogs, The Standard Method Equates Fitness with Relative Quality, Genetic Algorithms Generally Involve Many Choices, It Is Easy to Climb Bump Mountain Without Crossover, Crossover Enables Genetic Algorithms to Search High-Dimensional Spaces Efficiently, Crossover Enables Genetic Algorithms to Traverse Obstructing Moats, The Rank Method Links Fitness to Quality Rank, The Rank-Space Method Links Fitness to Both Quality Rank and Diversity Rank, The Rank-Space Method Does Well on Moat Mountain, Local Maxima Are Easier to Handle when Diversity Is Maintained, Conventional Wisdom Has Focused on Multilevel Description, Images Contain Implicit Shape Information, One Approach Is Matching Against Templates, For One Special Case, Two Images Are Sufficient to Generate a Third, Identification Is a Matter of Finding Consistent Coefficients, The Template Approach Handles Arbitrary Rotation and Translation, The Template Approach Handles Objects with Parts, The Template Approach Handles Complicated Curved Objects, Tracking Enables Model Points to Be Kept in Correspondence, Heuristics Help You to Match Unknown Points to Model Points, Averaged and Differenced Images Highlight Edges, Multiple-Scale Stereo Enables Distance Determination, Stereo Analysis Determines Elevations from Satellite Images, Reflectance Maps Embody Illumination Constraints, Making Synthetic Images Requires a Reflectance Map, Surface Shading Determines Surface Direction, Replacement Examples Support Binary Representation, Many Phrase Types Have the Same Structure, The X-Bar Hypothesis Says that All Phrases Have the Same Structure, A Theory of Language Ought to Be a Theory of All Languages, A Theory of Language Ought to Account for Rapid Language Acquisition, A Noun Phrase's Case Is Determined by Its Governor, Most Linguists Focus on Competence, Not on Performance, Analysis by Reversing Generation Can Be Silly, Construction of a Language Understanding Program Remains a Tough Row to Hoe, Syntactic Transition Nets Are Like Roadmaps, A Powerful Computer Counted the Long Screwdrivers on the Big Table, A Relational Database Makes a Good Target, Pattern Instantiation Is the Key to Relational-Database Retrieval in English, Moving from Syntactic Nets to Semantic Trees Simplifies Grammar Construction, Q&A Translates Questions into Database-Retrieval Commands, Relational Databases Consist of Tables Containing Records.
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