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Duluth Campus

Cognitive Science Minor

Philosophy
College of Arts, Humanities and Social Sciences
  • Program Type: Undergraduate free-standing minor
  • Requirements for this program are current for Fall 2017
  • Required credits in this minor: 18
Cognitive Science is the interdisciplinary attempt to understand the mind, especially the human mind (with the prospect of creating artificial minds coming in a close second). Understanding the mind and intelligence has long been a goal that seemed out of reach. The mind, consciousness, intelligence, and the related phenomena have been addressed by researchers in many areas including philosophy, psychology, linguistics, medicine, neuroscience, and artificial intelligence. These disciplines have very different histories and at universities are often separated by distance and academic culture. However, in the past 30 years, there has been a convergence of these disciplines on a few research paradigms: computational models of perception and reasoning, connectionism, and embodied cognition. It is now possible to form a more complete understanding of minds by drawing on contributions from all these disciplines, and a great deal of progress has been made. This has led to the rise at many universities of interdisciplinary programs in Cognitive Science. The programs exploit the insights that come from a variety of disciplinary approaches to understanding a single phenomenon: cognition. More specifically, Cognitive Science aims to understand the nature and development of such intelligent capacities as consciousness, perception, information processing, language acquisition and processing, planning, reasoning, learning, representation and use of knowledge, and problem-solving, whether these capacities are realized in biological or artificial systems. The Cognitive Science Minor looks to the theoretical foundations, the substantive empirical results, and the methodological tools of the contributing disciplines of Linguistics, Computer Science, Philosophy and Psychology. The hope of Cognitive Science is that by combining the methods and results of all these branches, we will be able to provide a global understanding of the mind, how it works, and why it works that way. Graduates of the minor program will be prepared for study in one of the many recently developed graduate Cognitive Science programs (including the Ph.D. offered at the Center for Cognitive Science at the University of Minnesota, Twin Cities) as well as graduate study in related programs such as cognition, brain, and behavior, cognitive neuroscience, artificial intelligence, and human-computer interaction. Those who choose to study the law, a path frequently chosen by philosophy majors, will be well suited for legal practice concerned with the variety of legal complexities associated with the development of these new technologies.
Program Delivery
This program is available:
  • via classroom (the majority of instruction is face-to-face)
Admission Requirements
A GPA above 2.0 is preferred for the following:
  • 3.00 already admitted to the degree-granting college
  • 3.00 transferring from another University of Minnesota college
For information about University of Minnesota admission requirements, visit the Office of Admissions website.
Minor Requirements
Core Requirement (3 cr)
PHIL 1025 - Introduction to Cognitive Science [NAT SCI] (3.0 cr)
Required Electives (15 cr)
Five courses across the listed subject areas, with the following stipulations: • Two courses maximum may come from any one listed subject area. • For the purposes of the minor: Computer Science (CS), Electrical Engineering (EE), Industrial Engineering (IE) and Mechanical Engineering (ME) will be considered as a single subject. • Students are advised to review course pre-requisites for upper-division electives.
Computer Science
Take no more than 2 course(s) from the following:
· CS 5222 - Artificial Intelligence (4.0 cr)
· CS 5232 - Introduction to Machine Learning and Data Mining (4.0 cr)
· CS 5242 - Natural Language Processing (4.0 cr)
Linguistics
Take no more than 2 course(s) from the following:
· LING 1811 - Introduction to Linguistics [LE CAT2, LOGIC & QR] (3.0 cr)
· LING 3102 - Syntax (3.0 cr)
· LING 3103 - Semantics and Pragmatics (3.0 cr)
· LING 4103 - Morphology: Word Structures and Rules (3.0 cr)
· LING 5400 {Inactive} (3.0 cr)
Philosophy
Take no more than 2 course(s) from the following:
· PHIL 1018 - Logic [LE CAT2, LOGIC & QR] (4.0 cr)
· PHIL 2011 - Philosophy of Language [LE CAT3, SOC SCI] (3.0 cr)
· PHIL 3570 - Philosophy of Psychology (4.0 cr)
Psychology
Take no more than 2 course(s) from the following:
· PSY 3061 - Physiological Psychology (4.0 cr)
· PSY 3520 - Introduction to Industrial/Organizational Psychology (3.0 cr)
· PSY 3611 - Learning and Behavior (3.0 cr)
· PSY 3613 - Applied Behavior Analysis and Behavior Change (3.0 cr)
· PSY 3621 - Cognition (3.0 cr)
· PSY 3661 - Psychology of Language (3.0 cr)
· PSY 3697 - Sensation and Perception (4.0 cr)
· PSY 5130 - Evolutionary Psychology (3.0 cr)
 
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· Cognitive Science Minor
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PHIL 1025 - Introduction to Cognitive Science (NAT SCI)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
The Cognitive Sciences investigate the mind from an interdisciplinary perspective using resources from such diverse disciplines as psychology, philosophy, computer science, and neuroscience. This class provides a general introduction to prominent theories/themes from Cognitive Sciences as well as a more detailed investigation of various select topics.
CS 5222 - Artificial Intelligence
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Principles and programming methods of artificial intelligence. Knowledge representation methods, state space search strategies, and use of logic for problem solving. Applications chosen from among expert systems, planning, natural language understanding, uncertainty reasoning, machine learning, and robotics. Lectures and labs will utilize suitable high-level languages (e.g., Python or Lisp). prereq: grad student, 2511, (2531 or 3512 or MATH 3355) or instructor consent, a grade of C- or better is required in all prerequisite courses
CS 5232 - Introduction to Machine Learning and Data Mining
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduction to primary approaches to machine learning and data mining. Methods selected from decision trees, neural networks, statistical learning, genetic algorithms, support vector machines, ensemble methods, and reinforcement learning. Theoretical concepts associated with learning, such as inductive bias and Occam's razor. This is a potential Master's project course. prereq: grad student, 2511, 2531 or 3512 or MATH 3355, Stat 3611 or 3411, Math 3280 or 3326 or instructor consent; a grade of C- or better is required in all prerequisite courses
CS 5242 - Natural Language Processing
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Techniques for creating computer programs that analyze, generate, and understand written human language. Emphasizes broad coverage of both rule-based and empirical data-driven methods. Topics include word-level approaches, syntactic analysis, and semantic interpretation. Applications selected from conversational agents, sentiment analysis, information extraction, and question answering. Significant research project that includes experimental results, written report, and clear grasp of ethical considerations involved. prereq: CS 2511, (2531 or 3512 or MATH 3355), grad student or instructor consent; a grade of C- or better is required in the prerequisite course; credit will not be granted if already received for CS 4242 or 5761
LING 1811 - Introduction to Linguistics (LE CAT2, LOGIC & QR)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Provides an introduction to a theoretical study of the nature of natural language, using examples primarily from present-day English. Students are expected to learn analytical skills to understand how human languages (and the human mind) work and how the sub-components (sounds, words, sentences and meaning) of natural languages are systematically organized.
LING 3102 - Syntax
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Deals with how sentences are structured. After discussing lexical categories (parts of speech) and phrasal structures from a scientific perspective, several different theories are introduced under the blanket name Generative Grammar. Based on Generative Grammar, students learn how to analyze English sentence structures to understand universal properties of natural language. prereq: 1811 or instructor consent
LING 3103 - Semantics and Pragmatics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
This course will provide an introduction to the study of what is said (semantics) and what is meant (pragmatics) in natural language. It will provide an introduction to set theory, first- and higher- order logic, and lexical semantics. It will also cover pragmatic topics such as presupposition, implicature, and speech act theory. Beyond these basic topics, the course will focus on specific sub-topics from time to time such as negation, reference, information structure, reported speech, genre, and so on. prereq: 1811
LING 4103 - Morphology: Word Structures and Rules
Credits: 3.0 [max 3.0]
Course Equivalencies: Ling 4103/Ling 5103
Grading Basis: A-F or Aud
Typically offered: Fall Odd Year
An introductory survey course on linguistic morphology that examines key concepts used to describe and explain the internal structures of words, and also deals with the central word formation processes across the typologically different languages. This theoretical knowledge acquired is then applied to the analysis of word formation in various discourse domains in present-day English and non-Indo-European languages. prereq: 1811, no grad credit
PHIL 1018 - Logic (LE CAT2, LOGIC & QR)
Credits: 4.0 [max 4.0]
Course Equivalencies: Phil 1018/1118
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduction to symbolic logic. Nature of language, species of arguments, informal versus formal arguments, techniques of translation, methods of sentential logic, and methods of predicate logic.
PHIL 2011 - Philosophy of Language (LE CAT3, SOC SCI)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Introduction to theories of meaning and truth and the structure of language. Relation of language to thought and the world; semantics and syntax; speech acts and performative utterances; descriptions and reference; and structuralism and the possibility of objective knowledge. prereq: Course in logic or literary analysis or human communication or CS or math or instructor consent
PHIL 3570 - Philosophy of Psychology
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Current philosophical issues surrounding psychology: behaviorism, dualism, mind/brain identity theories, computer models of cognition, and functionalism. prereq: 1001 or Psy 1003, 60 cr or instructor consent
PSY 3061 - Physiological Psychology
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Physiological basis of behavior, including central and peripheral nervous systems, sensory processes as they relate to perception, cognition, emotion, motivation, intelligence, and learning. prereq: 1003 or instructor consent
PSY 3520 - Introduction to Industrial/Organizational Psychology
Credits: 3.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Introduction to the field of industrial/organizational psychology. Major content areas within the field will be covered, including selection, training, performance evaluation, motivation, work stress, organizational culture, teams, and leadership. prereq: 1003 or instructor consent
PSY 3611 - Learning and Behavior
Credits: 3.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall, Spring & Summer
Study of basic learning and behavior processes including the evolution of behavior, pavlovian conditioning, instrumental learning, and elementary cognitive processes. prereq: 1003 or instructor consent
PSY 3613 - Applied Behavior Analysis and Behavior Change
Credits: 3.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall, Spring & Summer
Overview of diverse topics and application of the principles of the science of behavior known as behavior analysis. The philosophical system known as behaviorism that underlies this area of study will be explored, as well as the application of behavioral principles to a number of areas of society, including interpersonal relationship, parenting, clinical applications and treatments for persons with intellectual and other disabilities, business and management, animal behavior, health, sustainability, and more. Students will learn techniques for utilizing the principles of behavior in their own lives, conducting functional behavior assessments, as well as the social benefits associated with the incorporation of behavioral principles into educational, rehabilitative, organizational, and other settings. prereq: 1003
PSY 3621 - Cognition
Credits: 3.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall, Spring & Summer
An overview of cognitive processes, using historical, philosophical, biological, and experimental perspectives. Course topics include attention, perception, knowledge representation memory, language, thinking, reasoning, and decision-making. prereq: 1003 or instructor consent
PSY 3661 - Psychology of Language
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Psychological processes underlying comprehension, production, and acquisition of language(s); cognitive, social, biological, and educational perspectives on language and their applications. prereq: 1003 or instructor consent
PSY 3697 - Sensation and Perception
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Theories, methods, and findings in study of sensory and perceptual processes; psychophysics and psychophysiology of visual, auditory, gustatory, olfactory, cutaneous, kinesthetic, vestibular, and pain senses; analysis of perceptions of constancy, illusion, space, time, motion, and form. pre-req: PSY 1003 or instructor consent
PSY 5130 - Evolutionary Psychology
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Fall Odd Year
Evolution and the theory of natural selection as it applies to behavioral processes, e.g., survival, mating strategies, parenting and family, cooperation and conflict. prereq: psychology graduate student or instructor consent