Program tanımları
Objectives
Cognitive Science is defined as the scientific study of mind from an interdisciplinary perspective. The objective of our graduate programs is to offer students of different backgrounds breadth of knowledge and research techniques in a wide range of areas in Cognitive Science, including but not restricted to the areas of expertise of our staff.
The training we offer in Cognitive Science is interdisciplinary and theoretically oriented. Four disciplines are represented in the graduate programs of Cognitive Science at METU. Cognitive Psychology studies cognitive processes such as memory, attention, perception and reasoning through empirical research on human behavior. Linguistics investigates the nature of human language and its manifestation as a mental ability. Computer Science creates computational models of cognitive processes for purposes of understanding similar abilities in humans and designing intelligent systems. Philosophy addresses questions about the essential nature of mind, knowledge, representation, and language.
Career Opportunities
Language technology, innovative uses of computers, man-machine interfaces, academic track on Cognitive Science or related disciplines, such as Computer Science, Linguistics, Psychology, Philosophy.
Program Structure
Courses are grouped into four tracks. These are Computer Science, Linguistics, Psychology, Philosophy (see the curriculum). The advisor of each student will be responsible for guiding the student in taking the necessary courses, by considering the courses that the student has taken in the past. In order to receive a PhD degree, the total number of courses and credit hours taken in the master's and doctoral programs may not be less than 17 courses and 51 credit hours.
Degree Requirements
MS Degree Requirement
* 2 must courses (3 credits each)
* 4 restricted electives (3 credits each)
* 3 free electives (3 credits each)
* 1 Seminar course (non-credit)
* Master's Thesis (non-credit)
Graduate Curriculum
MS Program
Must Courses
Students must take COGS 501 - Linguistics and Formal Languages and COGS 502 - Logic and Programming courses.Students who have their undergraduate degree from Computer Science are exempted from COGS 502. Students with other undergraduate degrees who believe that
they can be exempted from this course because of their knowledge of the content of the course must see the course instructor.
Those students who are granted exemption from must courses must take an extra elective for each course replaced as such.
Students should take at least one restrictive elective from each track. All courses are offered by METU, except where noted.
Must Courses for MS and PhD Programs
Course Code: 9020501
Name: COGS 501 Linguistics and Formal Languages
Description: Natural language and linguistics knowledge. Language and grammar. Morphology. Syntax and grammatical structure. Semantics: Word meaning and grammatical meaning. Pragmatics: The grammar of discourse. Phonology.
Countable and countably infinite sets. Regular expressions and regular grammars. Finite-state machines. Context-free grammars. Push-down automata. Parsing and derivation: a brief introduction.
Type: Must
Course Code: 9020502
Name: COGS 502 Logic and Programming
Description: Sets, relations, and functions. Propositional and predicate logic. Truth, validity, and models. Deduction and inference methods. Introduction to intensional logic. Logic programming. Specification and construction of PROLOG programs. Various data structures and predicates of PROLOG. Overview of Functional programming.
Type: Must
Elective Courses for MS and PhD Programs
Track A: Computing
Course Code: 9020523
Name: COGS 523 Using Corpora for Language Research
Credit: 3
Description: The study of language via corpora. Definition and varieties of corpora. Building a corpus: sampling, representativeness, encoding and annotation. Characteristics of major available corpora. Using corpora: corpora in psycholinguistics, corpora and semantics, corpora and discourse, statistical natural language processing. Using tools and programming for corpus-based studies.
Type: Free Elective, track A
Course Code: 9020511
Name: COGS 511 Computational Models of Mind
Credit: 3
Description: An introduction to computational modeling in cognitive science, including computer simulation models of complex cognition, models within artificial intelligence, models based on neural mechanisms and networks, and formal and mathematical models in areas such as psychology, linguistics, and philosophy. Mathematical and computational modeling of the evolution of cognition. Models of cognition that extend beyond the boundaries of the person to include the environment, artifacts, social interactions, and culture.
Type: Restricted Elective, track A
Course Code: 5710584
Name: CENG 584 Cognitive Aspects of Natural Language Processing
Credit: 3
Description: Computational aspects of linguistic theories; Grammars and Parsing; Interpretation;
Information Structure; Ambiguity resolution; Interactions in multi-component grammars.
Type: Free Elective, track A
Course Code: 5710583
Name: CENG 583 Computational Vision Modeling
Credit: 3
Description: Introduction. Edges and Edge Detection. Segmentation. Texture. Stereo Imaging. Sequence of images. 3 Dimensional Vision. Applications.
Type: Restricted Elective, track A
Course Code: 5710582
Name: CENG 582 Advanced Neural Modeling
Credit: 3
Description: Mathematical treatment of generalization. Information theory in neural modeling. Radial-basis function networks. Higher- order neural networks. Adaptive resonance theory. Temporal processing in neural networks. Modular networks. Neurodynamics. Introductory computational neuroscience.
Type: Free Elective, track A
Course Code: 5710581
Name: CENG 581 Automated Reasoning
Credit: 3
Description: This course is intended to combine practice and theory in the fields of AI, logic, and mathematics which can be of interest to students and researchers involved in disciplines across these fields. Geometric reasoning, temporal reasoning, uncertain reasoning, non-monotonic reasoning, induction, meta-knowledge, and meta-reasoning, state and change, planning, intelligent-agent architecture.
Type: Restricted Elective, track A
Course Code: 5710569
Name: CENG 569 Neurocomputing
Credit: 3
Description: Learning and generalization. The basic perceptron and linear separability. Multilayer perceptrons and the back propagation algorithm. The Hopfield model and its dynamics. Bidirectional associative memory. Recurrent networks. Unsupervised learning and self-organizing maps. The counter-propagation network. Boltzmann machine and simulated annealing. Recent advances.
Type: Restricted Elective, track A
Course Code: 5710568
Name: CENG 568 Knowledge Engineering
Credit: 3
Description: Basic concepts and techniques. Knowledge representation. Drawing inferences. Tools and languages for expert systems. Knowledge engineering and expert systems development. Knowledge equization. Current expert system applications.
Type: Free Elective, track A
Course Code: 5710567
Name: CENG 567 Design and Analysis of Algorithms
Credit: 3
Description: Introduction to algorithms. The computational complexity of algorithms. Amortized analysis. Lower and upper bound theory. Approaches for designing algorithms: Divide-and-Conquer, Greedy Approach, Dynamic Programming, Backtracking and Branch-and-Bound. NP-Complete and NP-Hard problems. Approximation algorithms.
Type: Free Elective, track A
Course Code: 5710566
Name: CENG 566 Image Processing
Credit: 3
Description: Discrete time signals, and systems . Sampling, reconstruction, quantization. Digital image representation. Digital image fundamentals .Image transforms. Image enhancement. Image restoration. Image segmentation and description.
Type: Free Elective, track A
Course Code: 5710564
Name: CENG 564 Pattern Recognition
Credit: 3
Description: An introduction to the machine recognition of 1,2 or higher dimensional patterns. Statistical and linguistic approaches. Survey of application areas. Bayes Decision Theory. Decision boundaries, classifiers, and discriminant functions. Estimation of parameters. Clustering. Feature selection. Structural approaches to P.R. Neural networks recognizers. Applications.
Type: Free Elective, track A
Course Code: 5710563
Name: CENG 563 Computational Linguistics
Credit: 3
Description: Phrase structures, syntax, parsing. Semantics: Lambda-calculus, logic forms, compositional semantics, writing parsers and interpreters.Context-free grammars for Natural Language Processing. Definite-clause grammars.Basic concepts in morphology. Top-down and bottom-up parsing.
Type: Restricted Elective, track A
Course Code: 5710562
Name: CENG 562 Machine Learning
Credit: 3
Description: Paradigms of machine learning. Inductive, deductive, abductive forms of learning. Cognitive aspects of learning. Connectionist models of learning. Programming environments for learning programs.
Type: Free Elective, track A
Course Code: 5710561
Name: CENG 561 Artificial Intelligence
Credit: 3
Description: Problem solving and search strategies.Game playing. Knowledge representation.Expert systems and rule chaining. Vision. Natural language processing.Machine translation.Machine learning. Neural networks.
Type: Restricted Elective, track A
Course Code: 5670586
Name: EE 586 Artificial Intelligence
Credit: 3
Description: Exploiting natural constraints. Problem solving; Description matching and goal reduction, finding solution paths, games. Logic. Knowledge representation. Natural Language understanding. Applications of AI.
Type: Free Elective, track A
Course Code: 5670543
Name: EE 543 Neurocomputers
Credit: 3
Description: Introduction, computer models of neuron. Supervised and unsupervised learning, Hopfield nets, Perceptrons. Backprogation learning algorithms. Self organization and memories. Neurocomputing for pattern recognition, expert systems, and optimization problems. Analogy between Neurocomputers and computation in Cerebral Cortex. Characteristic differences between Digital and Neurocomputers.
Type: Free Elective, track A
Course Code: 5610509
Name: ES 509 Partial Differential Equations in Computer Vision/Image Processing
Credit: 3
Description: Axiomatic Approach in Computer Vision, Nonlinear Evolution equations, Representation of generic shape, Energy functions and associated Euler equations, Heat equation, multi resolution, stochastic connection. Prerequisite: Engineering Mathematics and working knowledge of a programming tool.
Type: Free Elective, track A
Course Code: 574
Name: BILKENT CS 574 Varieties of Formal Semantics
Credit: 3
Description: Beginning model theory. Non-classical logics. Brief review of the pioneering works of Godel, Church, Turing, Tarski, Kleene, Frege, Russel, Wittgenstein, et al. in philosophical logic and semantics. Determiners, quantifiers, conditionals, tense and modality, categorical grammars. Semantic automata. Counterfactuals. Montague's Intentional Logic. The Grammar of PTQ. Compositionality, partiality, nonexistent objects. Private languages, situation theory. Paradoxes. Model theory of common knowledge. Situated set theory.
Type: Free Elective, track A
Course Code: 563
Name: BILKENT CS 563 Computers and Commonsense Reasoning
Credit: 3
Description: Qualitative and quantitative knowledge in mechanics. Envisioning. Naive physics, histories, confluences, Kuipers 'Qualitative Simulation Theory. Forbus' Qualitative Process Theory. Comparative analysis and exaggeration. Mental models. Deep vs. shallow knowledge. Causality. Temporal notions. The problem of 'Generality in AI'.
Type: Free Elective, track A
Track B: Linguistics
Course Code: 8200506
Name: ELT 506 Second Language Acquisition
Credit: 3
Description: Surveying current research in language acquisition with special emphasis on similarities and differences between child and adult language, between native and foreign language acquisition.
Type: Free Elective, track B
Course Code: 8200520
Name: ELT 520 English-Turkish Contrastive Analysis
Credit: 3
Description: Introducing current approaches to contrastive analysis; comparing and contrasting English and Turkish in the areas of phonetics and phonology, syntax and semantics with special emphasis on problem areas in language teaching and learning.
Type: Free Elective, track B
Course Code: 8200608
Name: ELT 608 Pragmatics and Discourse Analysis
Credit: 3
Description: A linguistic perspective on major topics in pragmatics and discourse analysis: implicature; conversational structure; topic; information structure; coherence; context. Analysis of spoken and written language as an interactive process.
Type: Free Elective, track B
Course Code: 8200611
Name: ELT 611 Psycholinguistics
Credit: 3
Description: Current issues and theories in psycholinguistics focusing mainly on language and cognition, language acquistion, language processing, biological foundations of language, language disorders, and bilingualism.
Type: Free Elective, track B
Course Code: 9020522
Name: COGS 522 Lexical Semantics
Credit: 3
Description: Lexical semantics, history of lexical semantics, theta-roles, lexical conceptual structures, verb classes and alternations, lexical aspects, events, unaccusative hypothesis, ergative verbs, linking from lexicon to syntax
Type: Free Elective, track B
Course Code: 9020530
Name: COGS 530 Modern Theories of Grammar
Credit: 3
Description: The course introduces to the theory of principles and parameters which is representative for the contemporary discussion in linguistic research. Empirical adequacy and cognitive relevance are considered to be the relevant criteria of explanatory adequacy of a theory of grammar as a system of mental representations.
Type: Restricted Elective, track B
Course Code: 9020531
Name: COGS 531 Language and Cognition
Credit: 3
Description: Models for the acquisition, processing, and application of human knowledge as the object of cognitive sciences. Cognitive linguistics as the investigation of the acquisition, processing, and application of language knowledge. Grammar as a model of human language knowledge. Relations to artificial intelligence.
Type: Restricted Elective, track B
Course Code: 9020532
Name: COGS 532 Theoretical Linguistics
Credit: 3
Description: A survey of history of linguistics, sound-meaning structural relations in language, grammatical categories and functions, the role of linguistic explanation, formal theories of language, modern linguistics theories, computational complexity and linguistics theories, linguistic architectures and modularity, relation of language to mind and computation.
Type: Restricted Elective, track B
Course Code: 9020541
Name: COGS 541 Language Acquisition
Credit: 3
Description: The course aims to examine the theories and research methods in first language acquisition of phonology, morphology, syntax, semantics and pragmatics including representation of knowledge structures and bilingual processing.
Type: Restricted Elective, track B
Track C: Psychology
Course Code: 2330385
Name: PSY 385 Introduction to Cognitive Science
Credit: 3
Description: The course is intended to provide an introduction to multidisciplinary study of the human mind for diverse groups of students. Students will be exposed to the basics of how cognitive psychology, artificial intelligence, linguistics, neuroscience, and philosophy approach mental phenomena. The final portion of the course will present integrated approaches to some core topics of cognitive science such as language and vision.
Type: Free Elective, track C
Course Code: 9020535
Name: COGS 535 Cognitive Development
Credit: 3
Description: Development of infants (first 2 years of life) and pre-scholars (2-6 years). Theories of development (Nativist, empiricist, genetic epistemology dynamic systems theory (DST)). Basic concepts of development: knowledge representation, learning, maturation, modularity, domain-general vs. domain-specific development, emergence. Research methodology and experimental paradigms. Basic milestones in the development if perception (language, face, objects, action) and production (language, imitation of others and planning of own actions), categorization, understanding physical world, understanding human action, Theory of Mind (ToM), Reasoning/Logic, Causality, Attention and Memory (WM and LTM). Developmental cognitive neuroscience, brain development.
Type: Free Elective, track C
Course Code: 9020536
Name: COGS 536 Research Methods and Statistics for Cognitive Science
Credit: 3
Description: Research methods: The students will be introduced to basic concepts of empirical research and experimental design: independent/dependent variable(s), variance. Methods and methodology of psychological research: experiment, observation, ex-post-facto design, cross-sectional studies, longitudinal studies. Statistics: The students will be introduced to Descriptive Statistics: building statistical models, the relation between population-sample, distributions, various mean values, variance, SD, SE, confidential intervals, test statistics, as well as to Inferential Statistics: General Linear Model (GLM), various forms of Analysis of Variance (ANOVA, ANCOVA, MANOVA, repeated measures ANOVA, mixed design ANOVA). Correlation. Regression. Non-parametric tests. Factor analysis. Statistical analyses will be conducted using SPSS. Designing and reporting experiments.
Type: Restricted Elective, track C
Course Code: 9020551
Name: COGS 551 Human Memory
Credit: 3
Description: This course is intended to introduce the students to the theoretical, behavioral and anatomical study of memory. The course will start with a discussion of approaches, metaphors, and research methods in the study of memory. Special topics of concentration will include sensory memory stores, working memory and its components, encoding, storage, retrieval aspects of long term retention, and possibility of independent memory systems.
Type: Restricted Elective, track C
Course Code: 9020552
Name: COGS 552 Thought and Language Processes
Credit: 3
Description: This course will examine language, knowledge representation and thinking from the standpoint of behavioral research. Basic mental processes related to phonological, orthographic, syntactic and semantic processing will be examined. Rule-based and alternative approaches to human reasoning will be considered. The course will include discussions of specific topics such as logical reasoning, statistical reasoning, decision making, hypothesis testing, and problem solving. More general issues such as training in reasoning and expertise will also be discussed.
Type: Restricted Elective, track C
Course Code: 9020553
Name: COGS 553 Psychology of Reading
Credit: 3
Description: The course will review research on psychological processes related to reading starting from the more perceptual and proceeding towards conceptual and global issues. The early part of the course will deal with the control of eye movements and registration of visual information during reading. Then issues related to word identification such as alternative models of visual word recognition and possible role of phonological coding in visual word identification will be discussed. Other topics will include constructing mental representations from text, learning, reading, develop and acquired reading disabilities.
Type: Free Elective, track C
Course Code: 9020554
Name: COGS 554 Auditory Cognition
Credit: 3
Description: This course will concentrate on the perceptual and cognitive analysis of auditory stimuli at simple and complex levels. The early part of the course will be devoted to an introduction to the physical properties of sound and structure and functioning of auditory sense organs and the auditory nervous system. This will be followed by discussion of perception of simple qualities of sound as pitch loudness and timbre. The final part of the course will concentrate on more complex auditory phenomena such as auditory scene analysis, memory of auditory stimuli, perception of speech and perception of musical pitch.
Type: Free Elective, track C
Course Code: 9020555
Name: COGS 555 Connectionism and Human Behavior
Credit: 3
Description: This course will provide an introduction to connectionist models as a model of human behavior and mental process. The course will start with an introduction to the basic principles of connectionism, alternative structures and learning algorithms. Specific models that were developed in order to simulate human behavior in various areas such as vision, reading, speech perception, language and memory will be discussed. The course will conclude with a discussion of more general issues about connectionist models such as their viability as models of mental processes, their place in psychology today, and their relationship with the alternative models.
Type: Restricted Elective, track C
Course Code: 9020556
Name: COGS 556 Visual Cognition
Credit: 3
Description: The course covers sensory, perceptual, and cognitive processes related to vision from a mainly psychological viewpoint supported by neuroscientific and computational information where appropriate. Content includes discussion of theoretical approaches to vision and a survey of empirical research on main problems related to vision. Information on classic research will be supplemented by examination of contemporary research on central issues.
Type: Restricted Elective, track C
Track D: Philosophy
Course Code: 2410405
Name: PHIL 405 Philosophy of Language
Credit: 3
Description:Ordinary language and formal languages. Syntax, semantics, pragmatics. Extension and intension. Naming and predication. Theory of reference and theory of meaning.
Type: Free Elective, track D
Course Code: 2410507
Name: PHIL 507 Philosophical Logic I
Credit: 3
Description:Modal and intensional logics. Tense logic, epistemic logic, deontic logic.
Type: Restricted Elective, track D
Course Code: 2410508
Name: PHIL 508 Philosophical Logic II
Credit: 3
Description:A continuation of PHIL 507.
Type: Free Elective, track D
Course Code: 2410510
Name: PHIL 510 Topics in Epistemology
Credit: 3
Description:Study of selected topics in epistemology.
Type: Restricted Elective, track D
Course Code: 2410523
Name: PHIL 523 Studies in Philosophy of Science I
Credit: 3
Description:Discussion of various problems in contemporary philosophy of science. Critical assessment of recent philosophical views on these issues.
Type: Free Elective, track D
Course Code: 2410524
Name: PHIL 524 Studies in Philosophy of Science II
Credit: 3
Description:Discussion of various problems in contemporary philosophy of sicence. Critical assessment of recent philosophical views on these issues.
Type: Free Elective, track D
Course Code: 2410527
Name: PHIL 527 Philosophy in Science
Credit: 3
Description:The course is intended to provide information about the logical Empiricist philosophy of science, the origins of Logical Empiricism, confirmation, theoretical terms, explanation, falsification, the new image of science, perception and theory, presuppositions in science, scientific revolutions, context of discovery and context of justification, some basic epistemological and metaphysical problems in science, rationality, scientific knowledge and scientific truth.
Type: Free Elective, track D
Course Code: 2410621
Name: PHIL 621 Philosophy of Mind I
Credit: 3
Description:Logical analysis of ontological problems and main issues in the philosophy of mind.
Type: Restricted Elective, track D
Course Code: 2410622
Name: PHIL 622 Philosophy of Mind II
Credit: 3
Description:A continuation of PHIL 621.
Type: Free Elective, track D
Course Code: 2410632
Name: PHIL 632 Dynamics of Scientific Theories
Credit: 3
Description:Logical analysis of the evolution of physical theories.
Type: Free Elective, track D
Course Code: 2410633
Name: PHIL 633 Foundations of Logic I
Credit: 3
Description:Studies in the foundations of logical theories.
Type: Free Elective, track D
Course Code: 2410634
Name: PHIL 634 Foundations of Logic II
Credit: 3
Description:A continuation of PHIL 633
Type: Free Elective, track D
Course Code: 2410653
Name: PHIL 653 Theories of Scientific Method
Credit: 3
Description:Views on the methods of mathematical and empirical sciences in the ancient world; theories of method since Renaissance.
Type: Restricted Elective, track D
