• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
COMP4431 Artificial Intelligence
COMP4431 Artificial Intelligence

... applications; the development of formal logic; the Turing test; overview of AI application areas: game playing, automated theorem proving, expert systems, natural language understanding and semantics, planning and robotics, and machine learning. 2. Artificial intelligence as representation and searc ...
Multi-Instance Learning
Multi-Instance Learning

... S. Ray & D. Page (2001) showed that the problem of multiinstance regression is NP-Complete, furthermore, D. R. Dooly et al. (2001) showed that learning from real-valued multi-instance examples is as hard as learning DNF. Nearly at the same time, R. A. Amar et al.(2001) extended the KNN, Citation-kNN ...
A Formal Characterization of Concept Learning in Description Logics
A Formal Characterization of Concept Learning in Description Logics

... of concept names and role names) or if they are described on different levels of abstraction. Altogether it has turned out that for building and maintaining large DL KBs, besides the standard inferences, additional so-called non-standard inferences are required [27,19]. Among them, the first ones to ...
NLDB10-OntoGain - Intelligent Systems Laboratory
NLDB10-OntoGain - Intelligent Systems Laboratory

... C  value(a)   log 2 | a | ( f (a)  ...
Form 4.2 Faculty member + student Course syllabus for Artificial
Form 4.2 Faculty member + student Course syllabus for Artificial

... The Bachelor of Computer and Information Sciences in Computer Sciences ...
AI and Intelligent Systems
AI and Intelligent Systems

... • Does “intelligence” require a physical brain? – Programmed devices will probably never have “free will” ...
Lecture 2 - KDD - Kansas State University
Lecture 2 - KDD - Kansas State University

... Kansas State University Department of Computing and Information Sciences ...
Document
Document

... patterns in gene expression data Doesn’t interpret the patterns it finds in the context of the literature and the totality of relevant online quantitative data RelEx software for mapping English sentences into semantic structures Doesn’t do reasoning to resolve semantic ambiguity in a context-approp ...
CLEreg
CLEreg

... Blended Learning: Learning, training or educational activities where distance learning, in its various forms, is combined with more traditional forms of training such as “classroom” or in person training. CBL (computer-based learning): An umbrella term for the use of computers in both instruction an ...
building the future of finance with ai and machine
building the future of finance with ai and machine

... including SAS, Sybenetix and BT Radianz, there was a natural focus on the importance of data. In today’s increasingly complex market structure, any effective analytical model must be able to mine vast quantities of data very quickly, and this is a hurdle that must be overcome before the benefits of ...
Classical Conditioning
Classical Conditioning

... develop the skills they need to carry out their everyday roles within a broad range of community contexts, including living, learning, working, and social environments. A learning approach based on behavioral principles is commonly used to help people develop skills and gain mastery in these activit ...
Teaching AI through Machine Learning Projects
Teaching AI through Machine Learning Projects

... technology to enhance real-world applications within many of these topics. Machine learning also provides a bridge between AI technology and modern software engineering. In his article, Mitchell discusses the increasingly important role that machine learning plays in the software world and identifie ...
Introduction to Machine Learning
Introduction to Machine Learning

... Why “Learn” ?  Machine learning is programming computers to optimize a ...
Lecture 1 2015 INF3490/INF4490: Biologically Inspired Computing
Lecture 1 2015 INF3490/INF4490: Biologically Inspired Computing

... which is used by other ants to follow the trail. •  This kind of indirect communication via the local environment is called stigmergy. ...
Machine Learning Application in Robotics
Machine Learning Application in Robotics

... Supervised Learning ...
Course Outline - WordPress.com
Course Outline - WordPress.com

... The students would be required to divide themselves into groups. Both the assignments and the project are to be submitted collectively by the whole group. There would be three assignments, pertaining to the current contents that being taught in the course, with weightages of 3%, 3% and 4% respective ...
PPT
PPT

... In fact, the belief that neurophysiology is even relevant to the functioning of the mind is just a hypothesis. Who knows if we’re looking at the right aspects of the brain at all. Maybe there are other aspects of the brain that nobody has even dreamt of looking at yet. That’s often happened in the h ...
Learning Study Guide
Learning Study Guide

... Hand Luke”. Identify scenes from the movie that represents each drawback. Cognitive Learning What is Cognitive Learning? Who was Wolfgang Kohler? What is Insight Learning? Explain his experiment. What is Latent Learning? Who was Edward Tolman? Explain Explain his experiment. How do we use Cognitive ...
Learning Styles/Preferences
Learning Styles/Preferences

... Incorporate multimedia applications utilizing videos, images, or diagrams. ...
slides - Stanford Computer Science
slides - Stanford Computer Science

... objects, and parts? • What is the role of design vs. learning in recognition systems? ...
AP Psychology Outline Chapter 8: Learning
AP Psychology Outline Chapter 8: Learning

... a. How does operant conditioning work? What is operant behavior? b. B.F. Skinner's experiment demonstrated what? i. How does shaping tie in with Skinner? c. Reinforcement means what? i. What is an example of a positive reinforcement? Why? ii. What is an example of a negative reinforcement? Why? iii. ...
Teaching with the Brain-Based Natural Human Learning FACES
Teaching with the Brain-Based Natural Human Learning FACES

... Her first grade teacher thought she had ADHD and wanted her to take ritalin. I said no and began g to tutor her. I quickly ...
NNsML chap1
NNsML chap1

... Why Study Machine Learning? AI began as an attempt to understand the nature of intelligence, but it has grown into a scientific and technological field affecting many aspects of commerce and society. The main goals of AI & ML are: ...
Supervised learning
Supervised learning

... Thus, a neuron is going to separate the space of inputs with an hyperplan. This is why a neural network is good at classification. The action of a single neuron is quite easy ; only the cooperation of a great number of neurons can make complex tasks. ...
Teaching with the Brain-Based Natural Human Learning FACES
Teaching with the Brain-Based Natural Human Learning FACES

... stupid. With appropriate help she became an excellent reader. Only 5% of students have ADD, but more than 25% are given ritalin, which stifles normal brain growth. These students say they are so bored they can't sit still, be quiet, listen and obey; they want to think, figure things out themselves, ...
< 1 ... 48 49 50 51 52 53 54 55 56 ... 62 >

Concept learning

Concept learning, also known as category learning, concept attainment, and concept formation, is largely based on the works of the cognitive psychologist Jerome Bruner. Bruner, Goodnow, & Austin (1967) defined concept attainment (or concept learning) as ""the search for and listing of attributes that can be used to distinguish exemplars from non exemplars of various categories."" More simply put, concepts are the mental categories that help us classify objects, events, or ideas, building on the understanding that each object, event, or idea has a set of common relevant features. Thus, concept learning is a strategy which requires a learner to compare and contrast groups or categories that contain concept-relevant features with groups or categories that do not contain concept-relevant features.Concept learning also refers to a learning task in which a human or machine learner is trained to classify objects by being shown a set of example objects along with their class labels. The learner simplifies what has been observed by condensing it in the form of an example. This simplified version of what has been learned is then applied to future examples. Concept learning may be simple or complex because learning takes place over many areas. When a concept is difficult, it is less likely that the learner will be able to simplify, and therefore will be less likely to learn. Colloquially, the task is known as learning from examples. Most theories of concept learning are based on the storage of exemplars and avoid summarization or overt abstraction of any kind.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report