Research variant Cognitieve Science

Transcription

1 Research variant Cognitieve Science I

2 General information One of the programmes within the master Artificial Intelligence (AI) is that of Cognitive Science. To gain access to Cognitive Science you need a Bachelor Degree in Psychology, preferably within the area of Cognitive Psychology, or a Bachelor Degree in Artificial Intelligence. Alternatively, you can enroll with a Bachelor Degree in Neuroscience, Physics, Mathematics, Biology, Philosophy, Medicine, or Computer Science, provided you have an appropriate specialization. A Bachelor Degree in Clinical and Cognitive Neuropsychology or in Artificial Intelligence obtained at the VU guarantees admittance to Cognitive Science. Cognitive Psychology involves research in the areas of perception, attention, memory, learning, action, decision, and thinking. The major aim is to understand the processes that underlie human functioning. The research activities of the Department of Cognitive Psychology have a strong focus on visual and auditory perception, attention, and eye movements. Goals of the Program The programme focuses on the processes that underlie human functioning from two different research perspectives: empirical work and computational modelling. The combination of these two perspectives allows for a better understanding of the mechanisms underlying human functioning. For example, empirical work may suggest a functional layout for computation models, and vice versa, results of simulations with computation models can provide suggestions for setting up specific experiments. The underlying philosophy of Cognitive Science at the VU is to challenge students to be knowledgeable in a wide variety of fields and techniques, all of which are related to the subject area of cognitive psychology. Cognitive Science is jointly organized by the Department of Cognitive Psychology of the of Psychology and Education, and the Department of Artificial Intelligence of the of Sciences. Cognitive Science is a two-year Master allowing students to obtain a Master of Science (MSc). II

3 Inhoudsopgave Individuele vakken 1 Recommended Optional Courses 1 Compulsory Courses 1 Masterproject 2 AI Vervallen vakken History, philosophy & social aspects of science 2 Vak: Advanced Statistics for Experimentation 2 Vak: Behaviour Dynamics 3 Vak: Brain Imaging 4 Vak: Comparative Modeling 5 Vak: Evolutionary Computing 5 Vak: Experimental Design and Data Analysis 6 Vak: History and Philosophy of the Information Society 7 Vak: Human Ambience Innovation 7 Vak: Human Information Processing 8 Vak: Internet programming 9 Vak: Knowledge Management and Modeling 9 Vak: Master Project 10 Vak: Master Thesis: Research Project Cognitive Science 11 Vak: Memory and Memory Disorders 12 Vak: Mini Master Project AI 13 Vak: Model-based Intelligent Environments 13 Vak: Neural Models of Cognitive Processes 14 Vak: Perception 14 Vak: Project Agent Systems 15 Vak: Research methods 16 Vak: Review Paper 18 Vak: Scientific Writing in 18 Vak: Seminar Attention 20 Vak: Seminar Cognitive Neuroscience 21 Vak: Special Topics Cognitive Science 22 Vak: Thinking and Deciding 22 III

4 Individuele vakken Recommended Optional Courses Vakken: Naam Periode Credits Code Advanced Statistics for Experimentation Compulsory Courses Period P_MADVSTA Comparative Modeling 6.0 X_ Experimental Design and Data Analysis Human Ambience Innovation Periode X_ Periode X_ Internet programming Periode X_ Memory and Memory Disorders Period P_MMEMORY Mini Master Project AI Ac. Year (September) 6.0 X_ Model-based Intelligent Environments Periode X_ Perception Period P_MPERCEP Review Paper Period P_MREVPAP Seminar Attention Period P_MSEMATT Compulsory alongside the mentioned courses, are optional courses (18 credits) to complete 120 credits. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Opleidingsdelen: - Masterproject Vakken: Naam Periode Credits Code Behaviour Dynamics Periode X_ Brain Imaging Period P_MBRIMAG Evolutionary Computing Period X_ History and Philosophy of the Information Society Periode X_ Pagina 1 van 23

5 Human Information Processing Knowledge Management and Modeling Neural Models of Cognitive Processes Masterproject Period P_MHINFOP Period X_ Period P_MNEUMOD Project Agent Systems Periode X_ Research methods Periode 2, Periode X_ Scientific Writing in Seminar Cognitive Neuroscience Special Topics Cognitive Science Ac. Jaar (september), Periode 4, Periode 5, Periode X_ Period P_MSEMCNS Ac. Jaar (september) 12.0 X_ Thinking and Deciding Period P_MTHIDEC Students need to select one of the mentioned Master Projects. Note: Every programme, including the choice of optional courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Vakken: Naam Periode Credits Code Master Project Ac. Year (September) 30.0 X_ Master Thesis: Research Project Cognitive Science AI Vervallen vakken P_MTHRCSC History, philosophy & social aspects of science The choice of one of these elective courses, has to be discussed and agreed upon with the master coordinator or a personal mentor and approved by the Examination Board. Advanced Statistics for Experimentation Course code P_MADVSTA (815097) Period Period 4 Faculteit der Psychologie en Pedagogiek Coordinator dr. M. Gallucci Teaching staff dr. M. Gallucci Pagina 2 van 23

6 Teaching method(s) Lecture Course objective To acquire knowledge of and insight into statistics in order to be able to apply these techniques and read associated literature at a level relevant for research in cognitive neuropsychology. Course content This course provides a theoretical overview and detailed practical knowledge concerning statistical analyses of social psychological data. After an introduction of the general linear model, with emphasis on estimation of effect sizes and hypothesis testing, the course concentrates on applications of the model, such as analysis of variance, regression analysis, path analysis, and logistic regression. Along with these techniques, issues such as mediation, moderation, and hypothesis testing are considered. The aim of the course is to enable student to plan, execute, and interpret appropriate statistical analyses for applied and experimental research data. Because the application of advanced statistical techniques is central to the course, students will have several assignments to analyze existing data sets, and interpret the results. Form of tuition - H143 J., D144 P., West, S.I144G., & Aiken, L.S. (2003), Applied Multiple regression / I145G146correlation; analysis for the behavioural I147sciences (3rd ed. ) Hillsdale, NJ: Erlbaum; - H150Additional material provided during the course. Type of assessment Assignments and final examination. Course reading To be announced. Remarks Admission conditions: Statistics (or a similar course). Behaviour Dynamics Vakcode X_ (400113) Periode Periode 1+2 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator dr. O. Sharpanskykh Docent(en) prof. dr. J. Treur Lesmethode(n) Hoorcollege Doel vak To learn how to identify, specify and predict different types of behaviour; to understand how externally observable behaviour emerges from internal mechanisms; to be able to construct computational behavioural models and to perform analysis based on these models using software tools Pagina 3 van 23

7 Inhoud vak Behavioural dynamics occurs in different forms, contexts and complexity. During the course examples of such behaviour are studied coming from software systems (e.g., knowledge- and agent-based systems), cognition (e.g., the use of beliefs, desires and intentions, complex reasoning tasks) and organisation theory (e.g., organisational change). The dynamics of behaviour of such systems is analysed (including verification and validation), modelled and simulated in this course using different techniques and tools. Onderwijsvorm Combinations of lectures, practical assignments, and presentations. Toetsvorm Examination and practical assignments. Both grades should be at least 5. 5 to pass the course. Literatuur Online reader. Vereiste voorkennis Knowledge in mathematical logics (in particular, first-order predicate logic), logic programming Aanbevolen voorkennis Conceptual modelling skills; knowledge on agent-based systems Brain Imaging Course code P_MBRIMAG (815103) Period Period 5 Faculteit der Psychologie en Pedagogiek Coordinator dr. D.J. Heslenfeld Teaching staff dr. D.J. Heslenfeld Teaching method(s) Lecture Course objective To learn how various brain imaging techniques are used in modern neurocognitive research. Course content The course will treat physical principles, recording apparatus, and practical applications of the four major brain imaging techniques: EEG, MEG, MRI, PET, with an emphasis on EEG and MRI. These techniques will be discussed in detail and live demonstrated. We will visit the various labs, and students will perform a small research project of their own. This includes recording and analyzing your own brain imaging data in small supervised groups. Form of tuition Lectures and obligatory practicals Pagina 4 van 23

8 Type of assessment Written examination Course reading - Luck, S (2005) An introduction to the Event -Related Potential Technique Cambridge, MA: MIT Press - Huettel, S et al (2009) Functional Magnetic Resonance Imaging; (2 nd. ed. ) Sunderland, MA: Sinauer; Remarks Language: tuition in MRI practicals will take place on Wednesdays in the afternoon/evening. Comparative Modeling Vakcode X_ () Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator dr. T. Bosse Evolutionary Computing Course code X_ (400111) Period Period 1 Faculteit der Exacte Wetenschappen Coordinator prof. dr. A.E. Eiben Teaching staff prof. dr. A.E. Eiben Teaching method(s) Lecture Course objective To learn about computational methods based on Darwinian principles of evolution. To illustrate the usage of such methods as problem solvers and as simulation, respectively modelling tools.to gain hands-on experience in performing experiments. Course content The course is treating various algorithms based on the Darwinian evolution theory. Driven by natural selection (survival of the fittest), an evolution process is being emulated and solutions for a given problem are being "bred". During this course all "dialects" within evolutionary computing are treated (genetic algorithms, evolutiestrategieën, evolutionary programming, genetic programming, and classifier systems). Applications in optimisation, constraint handling and machine learning are discussed. Specific subjects handled include: various genetic structures (representations), selection techniques, sexual and asexual genetic operators, (self-)adaptivity. If time permits, subjects in Artificial Life and Artificial Societies, and Evolutionary Art will be handled. Hands-on-experience is gained by a compulsory pogramming assignment Pagina 5 van 23

9 Form of tuition Oral lectures and compulsory pogramming assignment. Type of assessment Written exam and pogramming assignment (weighted average). Course reading Eiben, A.E., Smith, J.E., Introduction to Evolutionary Computing. Springer, 2003 ISBN Slides available from Target group mba, mai, mcs, mpdcs Experimental Design and Data Analysis Vakcode X_ () Periode Periode 5 Voertaal Engels Coördinator dr. F. Bijma Docent(en) dr. F. Bijma Lesmethode(n) Hoorcollege Doel vak On completion of this course the student is able to: - design experiments and analyse the results by ANOVA - analyse data using linear regression or logistic regression models - perform basic nonparametric tests - perform these methods using a statistical package. Inhoud vak Regression models try to explain or predict a dependent variable using measured independent variables. Statistical methods are needed if there is random variation in the dependent variables. We will discuss multiple linear regression, analyses of variance (ANOVA) and logistic regression. All methods will be illustrated with practical examples. Especially in the case of ANOVA it is necessary that the study is well designed in order to draw sound conclusions from an experiment or survey. In this course a few well known designs (completely randomized, randomized block etc.) and the associated analyses of variance are discussed. The remainder of the course will be dedicated to non-parametric testing methods: - Wilcoxon test for (one and two samples) - Kolmogorov-Smirnov test (two samples) - rank correlation tests - permutation tests All analyses are carried out by a computer package, for which we need to know code but no formulas Pagina 6 van 23

10 Onderwijsvorm Lectures, practical exercises, discussion of the exercises Toetsvorm based on the written reports of the weekly and final assignments. Literatuur - slides of the lectures; - R manual; - assignments; - background reading to be announced. Aanbevolen voorkennis Empirische Methoden (X_401020) Doelgroep mai-cis, mai-cs, mai-ha, mai-ktiia, mai-tai, mcs-fmsv, mcs-hpdc, mcs- IWT, mcs-mm, mcs-se, mcs-tai Overige informatie All assignments are to be solved using the statistical package R ( History and Philosophy of the Information Society Vakcode X_ (405043) Periode Periode 2 Credits 3.0 Voertaal Engels Coördinator dr. ir. T. Koetsier Lesmethode(n) Hoorcollege Inhoud vak This course consists of two parts. Part one (3 credit points) is devoted to an "Introduction to the History and the Philosophy of the Information Age". Part one is taught by Teun Koetsier. Part two (1 credit point), devoted to the legal aspects of the information society, is taught by lawyers from the Computer/Law Institute of the Vrije Universiteit Human Ambience Innovation Vakcode X_ (405053) Periode Periode 2 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator dr. M.C.A. Klein Docent(en) dr. M.C.A. Klein Lesmethode(n) Hoorcollege Pagina 7 van 23

11 Inhoud vak This course provides an overview of possible application domains for Human Ambience. During the lectures, a number of experts in various domains (e.g., criminology, health, mental health, movement, social functioning) will provide background knowledge about these domains. Based on the presentations, the student is required to write reports, in which (s)he explains in detail how Human Ambience techniques can be applied to support humans in different domains. Onderwijsvorm Lectures. Toetsvorm exam. Literatuur Various papers. Doelgroep mai-is, mai-cs, mai-ws, mai-ha Human Information Processing Course code P_MHINFOP (815048) Period Period 1 Faculteit der Psychologie en Pedagogiek Coordinator dr. S.A. Los Teaching staff dr. S.A. Los Teaching method(s) Lecture Course objective Introduction to the major theories of human information processing and the experimental methods to test them. Course content In this course you will be familiarized with the literature on human information processing, which aims at understanding the functional architecture of processes intervening stimulus and response. Major themes include: (1) serial versus parallel organization of mental processes (2) continuous versus discrete transmission of information between consecutive processes (3) the controversity of the central bottleneck (4) the role of preparation and executive control. These themes are studied from a functional perspective: The focus is on what these processes are supposed to be doing rather than on where in the brain these processes are implemented. The dominant method in this literature is mental chronometry, which aims at making interfences on the basis of latency measures, such as response times and the onset of event- related brain potentials. Form of tuition Lectures Pagina 8 van 23

12 Type of assessment Open- ended written examination. Course reading Journal articles to be specified on Blackboard. Internet programming Vakcode X_ () Periode Periode 1 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator dr. S. Voulgaris Docent(en) dr. S. Voulgaris Lesmethode(n) Hoorcollege Doel vak Guide the student through the design and development of Network and Web applications. Inhoud vak The course discusses the principles for understanding, designing, and developing Internet applications. This includes programming the network (sockets, threads, RPC, RMI), programming the web interface (servlets, PHP, Javascript, AJAX), and setting up secure communication channels. Throughout the course, as well as in the context of the lab assignments, attention is paid to practical issues of applying these concepts. Onderwijsvorm Lectures combined with lab assignments Toetsvorm Final exam plus lab assignments Literatuur Course slides Vereiste voorkennis Knowledge of C, Java Aanbevolen voorkennis Systems Programming (X_400377) preferred: Computer Networks, Distributed Systems Doelgroep mai-cis, mai-cs, mai-ktiia, mai-tai, mcs-fmsv, mcs-hpdc, mcs-iwt, mcs- MM, mcs-se, mcs-tai, mpdcs Knowledge Management and Modeling Course code X_ (400125) Period Period Pagina 9 van 23

13 Faculteit der Exacte Wetenschappen Coordinator dr. A.C.M. ten Teije Teaching staff dr. A.C.M. ten Teije Teaching method(s) Lecture Course content Knowledge management is a relatively new discipline which has as its aim the efficiency improvement of the production factor "knowledge" and of the related business processes (knowledge creation, distribution, application and maintenance). The course "Knowledge Management and Modeling" is concerned with the organizational aspects of knowledge management, as well as the question how knowledge can be described with the support of modern information-modeling techniques. These knowledge models can be used to develop knowledge based systems. The notion of pattern-based knowledge modeling is a key issue in the knowledge management process. Students carry out a knowledge-management project in small project groups in a problem domain and organization of choice. Form of tuition Lectures, assignments, group project. Type of assessment Assignment, project reports. Course reading Schreiber, Akkermans, Anjewierden, de Hoog, Shadbolt, van de Velde, Wielinga: Knowledge Engineering & Management. The MIT Press, Cambridge MA, 2000, ISBN Target group mis, mai Master Project Course code X_ (400285) Period Ac. Year (September) Credits 30.0 Faculteit der Exacte Wetenschappen Course objective The Master programme in Artificial Intelligence is a scientific programme that aims to provide the student with the knowledge, experience and insights needed to autonomously carry out his/her professional duties. The programme is designed to prepare the student for further education as scientific researcher (Ph. D. studies) as well as to offer a solid basis for a career in business at an academic level. Moreover, the programme aims at educating the student as to acquire a practical understanding of the position of the field of Artificial Intelligence within a broad scientific, philosophic and social context Pagina 10 van 23

14 Course content Each Master AI programme is finished with a master project AI. This; can be an individual project as well as a group project. Information; about projects (incl. internships) can be found on the Internet pages; of the AI divisions. Internships proposed by the student him/herself; need approval in advance from a member of staff, who will also be; involved with supervising the project. The size of the graduation projects is as such that with adequate; foreknowledge and complete study, the project can be finished within; 6 months. The student participates in the KIM (Kunstmatige Intelligentie; Meeting). See blackboard KIM. Form of tuition The Master Project has always to be supervised by a staff member, in the case of an internship in cooperation with a supervisor in the company. Internships proposed by the student him/herself need approval in advance from a member of staff, who will cooperate with supervising the project. Type of assessment The final grade will be based on the quality of the research, the written thesis, the KIM presentations and the participation in the KIM. Target group mai Remarks For all rules, assessment criteria, contact persons, and many practical tips for your master project, see the KIM blackboard page (inclusive the "Manual for the Master Project AI"). Master Thesis: Research Project Cognitive Science Course code P_MTHRCSC (815067) Faculteit der Psychologie en Pedagogiek Coordinator prof. dr. J.L. Theeuwes Course objective To learn how to perform research and report about it. Projects involve basic research, applied research, research concerning modeling, or a combination of these. Course content Students participate in a research project concerning Cognitive Science. The Thesis can be done at the department of Cognitive Psychology (FPP), the department of Artificial Intelligence (FEW), an external research organization (for example TNO), a company, or another (foreign) university. Before starting, a written research plan should be submitted to the head of the department of Cognitive Psychology or the head of the department of Artificial Intelligence. Participation in a research project can only start after approval of the research plan. The Pagina 11 van 23

15 research performed by the student forms the basis for the Thesis. The Master Thesis should be written in article style. Students will be supervised by a person from the academic staff of the department of Cognitive Psychology or the department of Artificial Intelligence. There will be at least one meeting a week between the student and the supervisor. Type of assessment The final grade for the Master Thesis will be based on the quality of both the research and the written thesis. Grading will be done by the direct supervisor and the head of the department. It is required that students present their research in the form of a talk during a research meeting. Students are also required to attend at least four research meetings at the department of Cognitive Psychology. It is finally required that students participate in the KIM meetings according to the rules as outlined on the web- site of the KIM meetings. Memory and Memory Disorders Course code P_MMEMORY (815102) Period Period 2 Faculteit der Psychologie en Pedagogiek Teaching staff dr. R.J. Godijn Teaching method(s) Lecture Course objective The course aims to give students an overview of memory at the cognitive and neurophysiological level, and to give students the background to interpret memory disorders in patients with brain damage. Course content The course focuses on various approaches in the study of human memory and memory disorders. We will discuss working memory, encodingretrieval interactions, interference and forgetting implicit memory, and the brain substrate of memory. We will also discuss clinical testing of memory, and memory loss after local brain damage, dementia, and other conditions. Form of tuition 12 two- hour lectures and workshops and oral presentations. Type of assessment Exam and presentation. Course reading To be announced. Remarks This course will not be lectured in 2011/12. Students who have attended this course in 2010/11, but not succeeded yet, are granted one exam opportunity and presentation to successfully complete the course during 2011/12. Basically the exam is provided in the same period as last year. Take a look at VUnet or for the exact time schedule Pagina 12 van 23

16 Students have to contact their teacher to be able to make a presentation. The final result for the course will only be given if the exam as well as the presentation is passed. Mini Master Project AI Course code X_ (400428) Period Ac. Year (September) Faculteit der Exacte Wetenschappen Coordinator dr. M. Hoogendoorn Course objective Gaining deeper insight into a specific topic in AI. Course content This course consists of a small project on a specific topic in AI, selected in agreement with your supervisor. The project may have various forms, such as a literature study, the design of a piece of software, or exploring a research question. The results of the project are described in a brief report. To start, students should contact the coordinator of the projects: dr. M. Hoogendoorn (mhoogen@cs.vu.nl). Form of tuition Individual project and written report. Type of assessment The end grade is based on both the project and the written report. Target group mai-cis, mai-cs, mai-ktiia, mai-tai, mai-c-var Remarks Depending on the interest of the student, a specific topic is selected and an individual supervisor is assigned. Model-based Intelligent Environments Vakcode X_ (405056) Periode Periode 3 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator dr. M.C.A. Klein Docent(en) dr. M.C.A. Klein Lesmethode(n) Hoorcollege Inhoud vak During the bachelor Lifestyle Informatics, students have learned to model human processes using different techniques and at different levels of abstraction. In addition, they have learned to use such models for analysis of situations and reasoning about effective support. In this Pagina 13 van 23

17 course, the modeling knowledge will be further deepened and applied to a specific domain of scenario chosen by the student. The student will develop a prototype of an application based on models relevant for the scenario. By building this prototype, the students shows that he/she masters the modeling approaches and is able to apply this in a specific domain or scenario. Onderwijsvorm Lectures and assignments. Toetsvorm Assignments. Literatuur Papers Neural Models of Cognitive Processes Course code P_MNEUMOD (815051) Period Period 2 Faculteit der Psychologie en Pedagogiek Coordinator dr. M. Meeter Teaching staff dr. M. Meeter Teaching method(s) Lecture Course objective Neural network models have become part of the fabric of cognitive science, and have been applied in many domains. In this course, we will concentrate on these applications, and on hands- on experience with the development of neural network models. Course content The course will start with a general introduction, and a tutorial in a simulation environment. In the second part of the course, students will present published models, and be required to either extend a model or to do several exercises in the simulation environment. This work then has to be described in short papers. Form of tuition 22 hours lectures and discussion, 4 hours computer tutorial, one oral presentation, 30 hours group work, 10 hours activating work form. Type of assessment Grades are based on average of performance on a final exam, the oral presentation and the term paper. Course reading Syllabus, and a reader with recent papers. Remarks Period: 2 (in 2011/2012; NOT IN 2012/2013)! Perception Pagina 14 van 23

18 Course code P_MPERCEP (815047) Period Period 2 Faculteit der Psychologie en Pedagogiek Coordinator dr. C.N.L. Olivers Teaching staff dr. C.N.L. Olivers Teaching method(s) Lecture Course content Introduction to the fundamental principles of perception. Physiological, psychophysical and cognitive approaches to visual, auditory and tactile perception are treated. Is perception purely a registration of the outside world? Which processes and representations underlie conscious and unconscious perception? What methods can we use to find out? Form of tuition Lectures, literature study Course reading Goldstein, E.B. Sensation and Perception. 7th or 8th Edition. London: Wadsworth. As well as a selection of articles (to be announced in class). Project Agent Systems Vakcode X_ () Periode Periode 6 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator dr. M. Hoogendoorn Lesmethode(n) Hoorcollege Doel vak After completing the Project Agent Systems, the students have advanced skills in the design of agent systems. The student will be able to independently complete a number of steps when faced with a real-world problem for which a multi-agent system is to be designed: 1.The analysis of the problem domain, thereby acquiring sufficient knowledge to facilitate the first steps in the design of the multi-agent system. 2.The creation of a design of a multi-agent system, thereby taking preexisting architectures / generic models for agent systems into account. 3.The reporting of the design decisions and rationale behind them. 4.The implementation of the design. 5.The evaluation of the overall system. Inhoud vak The course consists of one main assignment in which a variety of important aspects that play a role in the design of multi-agent systems are reflected. More in particular, the assignment consists of the design Pagina 15 van 23

19 and implementation of an agent for the AAAI Poker competition (see Students can incorporate a variety of aspects within the design of this agent, for instance including (but not limited to) emotions, learning of opponent strategies, flexible switching between own strategies, etcetera. Students form groups of three (preferably covering a number of backgrounds, for instance a combination of more psychological backgrounds and more technical oriented ones) and are assigned a supervisor. During the first week the students analyze the domain and form idea about what to include in their agent. Each group then presents their initial ideas in front of the other groups. In the second and third week the design, the documentation of the design, and a first version of the implementation will be developed. The design will be based on or inspired by existing generic agent models. In the last week, the various implementations will be tested against each other and a winner is elected. The results of this competition (i.e. the performance of the agent) should be evaluated, and included in the report as well. Onderwijsvorm One large practical assignment in groups of 3-4 under supervision of a project leader. One start-up lecture will be given, and the students themselves have to present their initial idea during a presentation in the beginning of the second week. A final evaluation meeting (including the results of the competition) is also scheduled. Toetsvorm On the basis of the documentation and presentation. Literatuur Practical assignment, reader of the course Design of Multi-Agent Systems and the documentation associated with the AAAI Poker Competition. Aanbevolen voorkennis Some theoretical knowledge on the most important concepts within the design of multi-agent systems is advisable to participate in the course. Doelgroep mai-cis, mai-cs, mai-ha, mai-ktiia, mai-tai... Overige informatie More information can be found on Blackboard. Research methods Vakcode X_ () Periode Periode 2, Periode 5 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator prof. dr. J.M. Akkermans Docent(en) prof. dr. J.M. Akkermans Lesmethode(n) Hoorcollege Pagina 16 van 23

20 Doel vak This course helps students who want to embark on their Master research project and thesis. Inhoud vak The course provides an interdisciplinary overview of and hands-on work with different scientific research methods, with an emphasis on ICT/information systems and technologies in interaction with their human, social and organizational contexts. Topics are: - scientific research and its goals, the idea of scientific method; - developing and framing the research questions you want to answer; - making a research design and planning your research; - conceptualization, theory formation and validation/triangulation; - research methods and their assumptions, pros and cons (e.g. interview, observation, case study, field and action research, modelling and simulation, experiment, survey, statistical analysis); - how do you (and others) know that your research results are valid? - scientific argument, communication and research report writing. Onderwijsvorm In addition to lectures on various aspects of and issues in research methodology, students will get hands-on experience with different research methods. The setting of the practical work is that of a continuing research case investigation that emulates the different stages of a scientific research project. The research case question to be investigated is: What is it for systems to be considered "smart" or intelligent"? Toetsvorm Research project report, take-home written exam, active course participation (incl. self-report) Literatuur - Selection from Trochim s Social Research Methods Knowledge Base ( - Natasha Mack et al.: Qualitative Research Methods - A Data Collector's Field Guide - Andy Field: Discovering Statistics using SPSS - Digital resource of articles and excerpts on specific topics Vereiste voorkennis Basic knowledge of qualitative and quantitative research methods Doelgroep mai-cis, mai-cs, mai-ha, mai-ktiia, mai-tai, mis Intekenprocedure This course will be offered twice: in semester 1 at the FNWI and in semester 2 at the VU. Registration for courses at the FNWI is mandatory, but will be done by the Education Service Centre for the 1st year MSc students for courses of the first semester. See also and choose your master and then 'New procedure 'Registration for courses of Pagina 17 van 23

21 Science'. Registration for this course in semester 2 at the VU is mandatory and must be done at the VU (Free University) Review Paper Course code P_MREVPAP (815104) Period Period 3 Faculteit der Psychologie en Pedagogiek Coordinator dr. L.J.F.M. van Zoest Teaching staff dr. L.J.F.M. van Zoest Teaching method(s) Lecture Course objective To write a current literature review that covers an open issue in clinical or cognitive (neuro)psychology. Type of assessment The literature review is evaluated on the basis of the quality of paper and is graded by the internal supervisor. Course reading Depends on the topic of research during the Master Thesis. Scientific Writing in Vakcode X_ (400592) Periode Ac. Jaar (september), Periode 4, Periode 5, Periode 6 Credits 3.0 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Lesmethode(n) Hoorcollege, Werkcollege Doel vak The aim of this course is to provide the writing student with the essential linguistic means for producing academic texts which are effective, idiomatically and stylistically appropriate and grammatically correct. Inhoud vak The initial focus in the course lies on the form of scientific texts in the Exact Sciences: Abstract (or summary) Introduction Methods Results Discussion General course outline Introducing the topics Pagina 18 van 23

22 - Academic and technical writing in - The characteristics of different kinds of scientific texts - How scientific writing is judged and assessed - Where do you find your information and how do you present it? - How to avoid committing plagiarism Who am I writing for? What do I want to say? - Your readership - Key parts of an academic article: title, abstract, introduction, methods, results and discussion Writing the actual article - Paragraph and sentence construction: how do I link paragraphs together? - Writing simple and complex sentences. Active and passive sentences. - Argumentation : how do I put an argument? How do I frame my own opinion? Should I use I or we? Writing correct - Use of apostrophes and colons - Word order, verb tenses, time and tense - Avoiding mistakes typically made by Dutch writers - Common spelling mistakes You will be making considerable use of peer assessment: examining fellow students written work and giving them feedback. This method provides useful insights into how a text might be improved. The process of providing someone else with feedback on their text is something that you will find very instructive. Onderwijsvorm The course is focused on self-tuition. The plenary sessions concentrate on the process of writing and the product of writing. Homework is part of the course. With each topic, participants work through a phased series of exercises that usually conclude with the requirement to write a short piece of text. The instructor will append extensive written remarks to this text. Toetsvorm There will be no examination. However, students will receive their credits only when they have participated in all classes (presence is obligatory) and also when they have handed in the assignments satisfactorily. Students will receive a 'pass' when they have finished the course. Literatuur The reader `Writing a Scientific Article' can be obtained at the Taalcentrum-VU in the Metropolitan (4th floor). The costs are 20 euro. Vereiste voorkennis Bachelor Exact Sciences Doelgroep Compulsory for mai, mcs, mmns,mmath, mbmi & msfm. Optional for mis, mbio, mpdcs, mch, mdds, mphys. Overige informatie Registration for this course is only possible at the Educational Office of the of Exact Sciences. The usual registration deadlines are applicable, except for period 1. Registration for period 1 is possible until the 24th of August Pagina 19 van 23

23 Opening hours and contact information can be found here: Period 1 Optional: mai, mch, mcs, mdds, mis, mpdcs Period 2 Optional: mai, mch, mcs, mdds, mis, mpdcs Period 3 Compulsary: mmns Period 3 Optional: mai, mcs, mch, mdds, mis, mpdcs, mphys-amep, mphys- PLH, mphys-ppap Period 4 Compulsary: mmath, mba, msfm Period 4 Optional: mai, mch, mcs, mdds, mis, mpdcs, mphys-amep, mphys- PLH, mphys-ppap Period 5 Optional: mai, mch, mcs, mdds, mis, mpdcs, mphys-amep, mphys- PLH, mphys-ppap Period 6 Optional: mai, mch, mcs, mdds, mis, mpdcs, mphys-plh, mphys- PPAP Co-ordinator: drs J.K.A. Meijer Seminar Attention Course code P_MSEMATT (815100) Period Period 3 Faculteit der Psychologie en Pedagogiek Coordinator prof. dr. J.L. Theeuwes Teaching staff prof. dr. J.L. Theeuwes Teaching method(s) Lecture Course objective To learn how to interpret and analyze theories and findings on attention and eye- movements. Learn how to set up experiments. Course content The format of the seminar will be a discussion of one or two target articles, and student presentations, each week. Target articles for each week will be "classic" articles representing early and/or important studies on a specific topic or recent new papers in attention and eye movements. For the presentations, each student has to present the main findings of the target article for that week and is required to find a recent paper on the topic covered by the target article. Students have to prepare a 20 minute oral presentation in Microsoft Powerpoint. The rest of the class will be spent discussing the target articles and their relationship to the presented papers. Each student will give two presentations. The presentation will determine 30% of the course grade for each student. The target papers will be available on the course website and accessible via blackboard. One week after the last class, each student will submit a final paper (up to 8 pages, 12 pt. font, double spaced) on one of the topics covered in class. The paper will consist of a brief review of (at least) 6 research papers (including those already covered on that topic Pagina 20 van 23

24 in class) and a proposal for a new experiment. The paper will be worth 40%. Each class all students have to turn in a sheet of paper with a short question/ remark about one of the papers discussed during that class (30% of the grade). Form of tuition Lectures and practical assignments. Type of assessment Student presentation and writing a paper. Students are required to be present during all meetings. Attending the class is required. Course reading Articles. Seminar Cognitive Neuroscience Course code P_MSEMCNS (815098) Period Period 1 Faculteit der Psychologie en Pedagogiek Coordinator dr. A.V. Belopolskiy Teaching staff dr. A.V. Belopolskiy Teaching method(s) Lecture Course objective To extend students' knowledge in the field of cognitive and clinical neuroscience. Course content Over the last two decennia, scientific research in the field of cognitive neuroscience has led to fundamental new insights in the relation between brain function and behavior. Research is ongoing, and in many cases, the latest insights have not yet traversed their ways down into the regular textbooks. This seminar offers students the possibility to discuss state of the art research. The latest insights into topics such as working memory, multisensory perception, and the mirror neuron system will be covered. The seminar will also cover important questions regarding legal and ethical aspects of cognitive and clinical neuroscience research. Form of tuition Lectures, literature study, oral presentations and discussions. Type of assessment Oral presentation, contribution to discussion, and a review paper. Course reading Research papers to be announced. Remarks The requirement to participate is the completion of the basic Cognitive Neuroscience and Neuropsychology course. Alternatively, Pagina 21 van 23

25 students may study the required literature by self- study. You need to contact the professor of Seminar Cognitive Neuroscience beforehand. Before you can enter the Seminar, you will need to pass an oral exam with the professor. Note that it is your own responsibility to contact the professor, study the literature and make an appointment for the oral exam. Special Topics Cognitive Science Vakcode X_ () Periode Ac. Jaar (september) Credits 12.0 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator dr. T. Bosse Inhoud vak The aim of this course is to eliminate specific deficiencies in the areas of Artificial Intelligence and Cognitive Psychology. Each student will take part in an individually developed course consisting of a range of topics covering the basics of Artificial Intelligence, Cognitive Psychology, or both, depending on the specific deficiencies present. In order to determine the individual content of the course program, students are required to make an appointment with the course coordinator. The individually tailored course program will contain (a subset of) the following elements: principles of programming, propositional and predicate logic, knowledge- based systems, multi-agent systems, cognitive neuroscience and neuropsychology, and principles of (experimental) research design. Although most of these elements address basic principles of Artificial Intelligence or Cognitive Psychology, the pace and the difficulty of the program will be at Master level. Onderwijsvorm Lectures, tutorials. Toetsvorm Individual assessments. Literatuur Dependent on individual. Doelgroep mai-cs Thinking and Deciding Course code P_MTHIDEC (815049) Period Period 2 Faculteit der Psychologie en Pedagogiek Coordinator L. Zwaan Teaching staff L. Zwaan, L. Claassens MSc Pagina 22 van 23

26 Teaching method(s) Lecture Course objective Explaining and providing understanding of theories, research methods and practical aspects about human judgment, rational thinking, dilemmas and choices. Course content Why do we make certain decisions? What is rational thinking, and what keeps us from it? How can we improve our thinking and decision processes? How do we reason and choose in uncertain (risk) situations? What is the influence of (moral) beliefs and emotions? Form of tuition Lectures, literature study, oral presentations and discussion. Type of assessment Oral presentation, contribution to discussion, and a review paper. Course reading A selection of articles and book chapters Pagina 23 van 23