Computer Science Course Descriptions for Fall of 1997
CMPSCI 102: Computers and Society (R2)
There are three principal components to this course: 1) what computers are, 2) how they are used in society, and 3) how their use affects society. In the first part we explore the origin of computers and the historical, economic, and scientific forces that brought them into existence. We also study the essential hardware components that make up a computer and we learn the basic software methods of programming using the BASIC language. In the second part, usage of computers by business in the office and in factory automation, by the professions such as medicine, and by artists and scientists is covered; special attention is given to the advent of the Information Super Highway, how to use it and how it can benefit individual users. Finally the economic and socio-political impact that computers are having on society and on the individual are discussed; these issues range from questions of privacy to the impact of robots in the factory, to the use of computers in political action. The primary aim of the course is to impart sufficient computer literacy to enable the student to 1) write simple, but non-trivial programs, 2) make use of and benefit from available computer facilities, and 3) understand why computers have become such a powerful force in the modern society. 3 credits.
CMPSCI 105: Computer Literacy (R2)
Microcomputers are now used widely not only in academia but in all areas of modern life. For this reason it's important that all students understand how computers work and how computers can be used as a problem-solving tool. The focus of this course is on computer applications. The course stresses the ways in which computers can help you solve problems efficiently and effectively. The course provides a broad introduction to hardware and software aspects of microcomputers. Then four application areas are discussed: word processing, spreadsheets, databases and telecommunications (access to the Internet). The course uses the university's microcomputer labs, and weekly 90 minute lab sessions are an integral part of the course. Students who are more interested in computer programming should take CMPSCI 121 or 187. Prerequisites: reasonable high school math skills. Typing ability is also an important asset for the course. Previous computer experience is not expected. 3 credits.
CMPSCI 105C: Computer Literacy (R2)
CMPSCI 105W: Computer Literacy (R2)
CMPSCI 105X: Computer Literacy (R2)
CMPSCI 121: Introduction to Problem Solving with Computers (R2)
An introductory course in problem solving and computer programming using the programming language Pascal. The course focuses on the fundamental concepts of problem solving and the techniques associated with the development of algorithms and their implementation as computer programs. This course or its equivalent is required for all additional courses in CMPSCI. Three hours of lecture/recitation per week. About 6 programming problems are assigned. In addition there are assigned homework problems, amid-term exam and a final. No computer science prerequisite, although high school algebra and basic math skills (e.g. R1) are assumed. Use of computer is required. 3 credits.
CMPSCI 121D: Introduction to Problem Solving with Computers (R2)
CMPSCI 187: Programming with Data Structures (R2)
The course introduces and develops methods for designing and implementing abstract data types. The main focus is on how to build and encapsulate data objects and their associated operations. Specific topics include pointer variables, linked structures, recursive structures and algorithms, binary trees, balanced trees, and hash tables. There will be weekly assignments, consisting of programming and written exercises, a midterm, and a final exam. Prerequisites: CMPSCI 121 (or equivalent) and Basic Math Skills (R1). 4 credits.
CMPSCI 187D: Programming with Data Structures (R2)
CMPSCI 191A: Seminar - Practical Skills for the Internet
The Internet is a goldmine of information and software resources for those who know how to plug into it and navigate it. Originally designed for computer scientists, the net is now open to the general public through educational computing accounts and commercial services. Unfortunately, much of the enabling technology associated with net navigation is still aimed at computer specialists. This course will provide non-CS majors with the basic skills needed to tap the net. We will cover basic UNIX commands, e-mail management, listserv software, gophers, Usenet newsgroups, ftp file transfers, telnet sessions, www browsers, basic web page design, and PGP-based cryptography. Students will also work with a number of search tools including veronica, archie, wais databases, and www search engines. In addition, we will survey key social and political topics that are relevant to the Internet, such as copyright law, First Amendment issues, computer security, personal privacy, electronic cash, commercialization, and bandwidth pricing strategies. Prerequisites: some hands-on experience with PCs or MACs or UNIX (programming experience is NOT required). 3 credits.
CMPSCI 191D: Seminar - TAP Program
Conversations with members of the UMass CMPSCI community, to explore issues in and subareas of computer science. Open only to first-year students in the CMPSCI TAP residential program. 1 credit.
CMPSCI 201: Architecture and Assembly Language (E)
Lecture, lab. The architecture and machine-level operations of modern computers at the logic, component, and system levels: topics include binary arithmetic, logic gates, Boolean algebra, arithmetic-logic unit, control unit, system bus, memory, addressing modes, interrupts, input-output, floating point arithmetic, and virtual memory. Simple assembly language is used to explore how common computational tasks are accomplished by a computer. Three hours of lecture and one or two lab sessions per week, laboratory exercises, homework exercises, two midterm exams, and a final exam are required. Prerequisite: CMPSCI 187 or equivalent. 4 credits.
CMPSCI 250: Introduction to Computation (E)
Lecture, discussion. Basic concepts of discrete mathematics useful to computer science, with the theory of regular languages and finite-state machines as the prime motivating example. The language of mathematics: Set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: Interplay of inductive definition, inductive proof, and recursive algorithms. Elementary combinatorics. Basic graph theory. Finite-state machines and regular languages: Myhill-Nerode Theorem, nondeterministic finite automata, Kleene's Theorem. Problem sets, 2-3 midterm exams, timed final. Corequisite: MATH 132/136 or equivalent. Prerequisite: CMPSCI 187 or equivalent. 4 credits.
CMPSCI 287: Programming Language Paradigms
Lecture, discussion, programming projects, lab. Programming Language Paradigms provide a basic philosophy to support the construction of reliable large-scale systems. This course discusses four such paradigms. In the -functional paradigm- software is constructed in such a way as to minimize the use of side-effects, thereby simplifying the conceptual structure of programs and making them easier to analyze and understand. The -logic paradigm- supports the development of software in which the concept of -relation- (for example a relation between people) is more important than the concept of function. In the -imperative paradigm- we are concerned with principled ways in which software that is state-dependent can be constructed. Finally, in the -object-oriented- paradigm we are concerned with combining data with code to create "objects" which exhibit behavior. Prerequisite: CMPSCI 187. Corequisites: CMPSCI 250 and MATH 132. 4 credits.
CMPSCI 311: Introduction to Algorithms
This course will introduce you to algorithms in a variety of areas of interest, such as sorting, searching, string-processing, and graph algorithms. You will learn to study the performance of various algorithms within a formal, mathematical framework. There will be a few programming assignments as well to help you relate the empirical performance of an algorthim to theoretical predictions. Mathematical experience (as provided by CMPSCI 250) is required. You should also be able to program in Pascalor C (or some other closely related language). 4 credits.
CMPSCI 320: Introduction to Software Engineering
In this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semester-long team project in which a software development project is carried through all the stagesof the software life cycle. Topics in this course include requirements analysis, specification, design, abstraction, programming style, testing, maintenance, and software project management. Particular emphasis is placed on designing and developing maintainable software and on the use of object-oriented techniques throughout the software lifecycle. Use of computer required. Two exams, several homeworks, major term project. Prerequisite: CMPSCI 287. 4 credits.
CMPSCI 377: Operating Systems
In this course we examine the important problems in operating system design and implementation. The operating system provides a well-known, convenient, and efficient interface between user programs and the bare hardware of the computer on which they run. The operating system is responsible for allowing resources (e.g., disks, networks, and processors) to be shared, providing common services needed by many different programs (e.g., file service, the ability to start or stop processes, and access to the printer), and protecting individual programs from one another. The course will start with a brief historical perspective of the evolution of operating systems over the last fifty years, and then cover the major components of most operating systems. This discussion will cover the tradeoffs that can be made between performance and functionality during the design and implementation of an operating system. Particular emphasis will be given to three major OS subsystems: process management (processes, threads, CPU scheduling, synchronization, and deadlock), memory management (segmentation, paging, swapping), file systems, and operating system support for distributed systems. Assignments: 3 labs in C++, 3 exams, 6 or more written homeworks. Prerequisites: CMPSCI 187, CMPSCI 201. 4 credits.
CMPSCI 377X: Operating Systems
CMPSCI 383: Artificial Intelligence
Introduction to techniques for building intelligent machines: problem solving, state-space representation, heuristic search techniques, game playing, knowledge representation, logical reasoning, planning, reasoning under uncertainty, learning, expert systems, natural language processing, image understanding. Prerequisites: CMPSCI 250 and CMPSCI 287. 3 credits.
CMPSCI 391F: Seminar - HTML for Poets
An exploration of the Hyper Text Markup Language and its philosophical implications for Society at the threshold of the year 2000. Java Script will also be discussed. Students cannot receive credit for both this course and CMPSCI 591_ Seminar-HTML forPoets. 3 credits.
CMPSCI 396A: Independent Study - Debugging and Consulting
In this course we teach students how to consult on topics involving E-mail, e.g., Pine or Goldmail or Mail; Operating Systems such as VMS and Unix; Editors such as LSE and Pico; one computer language: BASIC; and some elementary HTML. Necessary skills on how to debug Home Pages written in HTML and simple but non trivial programs written in BASIC are also acquired. Consultants are required to attend all weekly meetings [mandatory], consult with CMPSCI 102 students to review basic concepts and help debug programs [2 hrs minimum weekly at a terminal]. Consultants are also required to grade programming assignments [6 for each student]. In general each consultant will be responsible for no less than 6 students. May not be repeated for credit more thantwice. 3.0 credits.
CMPSCI 405: Social Issues in Computing
Designed to satisfy the Junior Year writing requirement, CMPSCI 405 introduces the student to technical writing and editing, scientific journalism and the social essay. The course combines practical, scientific writing as found in industry and businesswith explorative essays that focus attention upon the technological and humanistic concerns inherent in society. Ten written assignments-two longer papers, eight shorter ones and one oral presentation. 3 credits.
CMPSCI 410: Compiler Techniques
This course explores the basic problems in the translation of programming languages focusing on theory and common implementation techniques for compiling traditional block structured programming languages to produce assembly or object code for typical machines. The course involves a substantial laboratory project in which the student constructs a working compiler for a considerable subset of a realistic programming language. The lectures are augmented by an optional laboratory section that covers details of the programming language used to build the compiler, the operating system, the source language, and various tools. Use of computer required. Text: Crafting a Compiler in C, by Fischer and LeBlanc. Prerequisite: CMPSCI 377 or 402. 3 credits.
CMPSCI 445: Information Systems
Introduction to database systems. File organization, database system architectures, data models, database design, relational systems, query optimization, recovery and concurrency control. Prerequisite: CMPSCI 287. 3 credits.
CMPSCI 445X: Information Systems
CMPSCI 520: Software Engineering
Software Engineering I: This course introduces students to the principal activities involved in developing high-quality software systems. The course stresses the use of defined, systematic processes in the creation of carefully defined and engineered software products. Among the topics covered are requirements analysis, formal specification methods, process definition, software design methods, and test planning. Issues specific to the development of software by teams and groups will also be addressed. Students will be required to read selected papers from the literature and complete homework projects. This course focuses on synthesis activities and complements Software Engineering II, which focuses on software analysis techniques. Students areencouraged to take both courses but may take either course independently. Students who sign up for 620 will be expected to do more comprehensive projects than those who sign up for 520. 3 credits.
CMPSCI 520X: Software Engineering
CMPSCI 521X: Advanced Software Engineering
CMPSCI 530: Programming Languages
CMPSCI 535: Computer Architecture
The structure of digital computers is studied at several levels, from the basic logic level, to the component level, to the system level. Topics include: the design of basic components such as arithmetic units and registers from logic gates; the organization of basic subsystems such as the memory and I/O subsystems; the interplay between hardware and software in a computer system; the von Neumann architecture and its performance enhancements such as cache memory, instruction and data pipelines, coprocessors, and parallelism. Weekly assignments, semester project, 2 hours exams, final. Prerequisites: CMPSCI 201 and CMPSCI 250. 3 credits.
CMPSCI 570: Computer Vision
What is computer vision and why is it an important and interesting area of study. The basic building blocks and algorithms of computer vision. The processes of image formation and the relationship of images to the three-dimensional world. Enhancing images for human viewing. Extracting edges and lines from images. Morphological operations on images. Extracting regions from images. The basic principles of convolution and correlation. Measuring color, texture, shape, size, and other features of images and image components. The principles of perceptual organization and their role in computer vision. Prerequisite: calculus and linear algebra. 3 credits.
CMPSCI 572: Neurobiology
Lecture. Biology of nerve cells and cellular interactions in nervous systems. Lectures integrate structural, functional, developmental, and biochemical approaches. Topics include neuronal anatomy and physiology, membrane potentials, synapses, development of neuronal connections, visual system, control of movement, and neural plasticity. Text: Essentials of Neural Science, Kandel et al. ; reserve readings, 2 hour-exams, final, short critique paper. Prerequisite: Biology 285 or 523; or both PSYCH 330 and Intro. Biology. 3 credits.
CMPSCI 591C: Embedded Systems
Professor: Grupen, Popplestone
Most computers in use in the world are embedded in a system whose primary purpose is not to serve as a computer. Devices varying from the an aircraft like the Boeing 777 to VCR's and Microwave Ovens are absolutely dependent upon embedded processors forvital control functions. These computing applications do not require the same specifications as general purpose computational platforms, but are instead intimately related to a particular physical process. This course attempts to introduce the tools necessary to design embedded computational applications. Topics include: (1) mechanisms, sensors, actuators and feedback systems, (2) analog and digital circuits, power amplifiers, signal processing, operational amplifiers, multiplexing, (3) I/O - A/D, D/A, latching, serial and parallel interfaces, DMA, and (4) signal processing/conditioning. There will be a 3 credit lecture and a 1 credit lab (required) in which a hands-on, team project for an embedded application will be constructed over the semester. 3 credits.
CMPSCI 591D: Seminar - Three-Dimensional Animation and Digital Editing
This seminar is dedicated to the production of high quality computer animation using microcomputer based 3-dimensional graphics technology. For example, color 3-D objects are defined and manipulated, digitized images created and altered, and animated sequences produced directly on the computer. Techniques are used to bend and twist shapes around objects or lines and to trace over images including digitized pictures. The course is directed at production of an informative and approachable video of a ten minute 3-dimensional animated piece. Using computer-generated graphical analogies as well as cartoon caricature, the video is designed to educate and entertain. 3 credits.
CMPSCI 591N: Embedded Systems Lab
Professor: Grupen, Popplestone
Required Lab for CMPSCI 591C Embedded Systems. 1 credit.
CMPSCI 596A: Independent Study - Advanced Software Engineering
CMPSCI 596X: Independent Study
CMPSCI 610: Compiler Techniques
This course explores the basic problems in the translation of programming languages focusing on theory and common implementation techniques for compiling traditional block structured programming languages to produce assembly or object code for typical machines. The course involves a substantial laboratory project in which the student constructs a working compiler for a considerable subset of a realistic programming language. The lectures are augmented by an optional laboratory section that covers details of the programming language used to build the compiler, the operating system, the source language, and various tools. In addition to lectures in common with CMPSCI 410 (491A), CMPSCI 610 includes an extra weekly meeting covering the theoretical aspects in greater depth. Use of computer required. Text: Crafting a Compiler in C, by Fischer and LeBlanc. Prerequisite: CMPSCI 377 or 402. 3 credits.
CMPSCI 611: Advanced Algorithms
Principles underlying the design and analysis of efficient algorithms. Design paradigms: divide-and-conquer, dynamic programming, greedy algorithmics, the role of randomization. Analysis paradigms: worst-case, average-case, and amortized analyses. Other important themes: network flow, coping with computational intractability (NP-hardness), parallel algorithmics. Problem domains covered include sorting and searching, graph algorithms, and scheduling problems. PREREQUISITES: Mathematical sophistication expected of incoming CMPSCI graduate students, equivalent at least to an A in CMPSCI 250; knowledge of programming and data structures at the level of CMPSCI 187; knowledge of algorithms at the level of CMPSCI 311. 3 credits.
CMPSCI 611X: Advanced Algorithms
CMPSCI 620: Advanced Applications of Software Engineering
Software Engineering I: This course introduces students to the principal activities involved in developing high-quality software systems. The course stresses the use of defined, systematic processes in the creation of carefully defined and engineered software products. Among the topics covered are requirements analysis, formal specification methods, process definition, software design methodolgies, and test planning. Issues specific to the development of software by teams and groups will also be addressed. Students will be required to read selected papers from the literature and complete homework projects. This course focuses on synthesis activities and complements Software Engineering II, which focuses on software analysis techniques. Students are encouraged to take both courses but may take either course independently. Students who sign up for 620 will be expected to do more comprehensive projects, that emphasize critical and analytic thinking, than those who sign up for 520. 3 credits.
CMPSCI 650: Empirical Methods for Computer Science
The purpose of this course is to increase the number of people in computer science who can design and run informative experiments. We begin with data and exploratory data analysis, not experiments proper, because the experiment is only one step, typically confirmatory, in an ongoing empirical research programme. The experiment follows (and often precedes) assessment and exploratory studies in which we develop and refine causal models of the behaviors of our programs. Thus, the first part of the course addresses techniques for visualizing, summarizing and detecting clues about causal relationships in data. Next we study how to design a controlled experiment. In principal, programs are ideal subjects because we can cripple and maim them on the altar of control without fear of censure, but in practice, we must often forego classical manipulation experiments for more equivocal observation experiments. The third part of the semester is a crash course in statistics, and the fourth part is organized around common research questions: is this algorithm faster than that one? under which conditions will this planner fail? what affects the ratio of hits to false positives in this binary choice task? is the dependency between these factors robust? does this learning curve rise more steeply than that one? We will show how to design experiments to answer these questions and analyze the data with the appropriate statistical tools. (By the way, we will cover not only classical statistics but also non parametric and computer-intensive techniques like bootstrapping.) The fifth part of the course is concerned with statistical methods for inducing causal models of how our systems work. Although the sixth and last part is devoted to the question, "what makes a result general," you will discover that this question drives the entire course. The course is meant to be practical. It emphasizes techniques, tactics and case studies. Homework is designed to provide practice, and each student must complete a project (ideally related to ongoing research), write it up and present it. Most of the examples in my lectures are from Artificial Intelligence, but the course is more general in its scope, and I encourage students from other areas of computer science to take it. The text is my own. 3 credits.
CMPSCI 650X: Empirical Methods for Computer Science
CMPSCI 653X: Computer Networks and Distributed Processing
CMPSCI 683: Artificial Intelligence
In-depth introduction to Artificial Intelligence focusing on techniques that allow intelligent systems to operate in real-time and cope with missing information, uncertainty, and limited computational resources. Topics include: advanced search and problem-solving techniques, resource-bounded search, principles of knowledge representation and reasoning, meta-reasoning, reasoning under uncertainty, Bayesian networks and influence diagrams, decision theory and the value of information, perception and interpretation problems, planning and scheduling, intelligent agents architectures, and learning. Prerequisites: Undergraduate background in Computer Science, and an undergraduate Artificial Intelligence course (CMPSCI 383 or equivalent). 3 credits.
CMPSCI 683X: Artificial Intelligence
CMPSCI 691C: Seminar - Interactive Multimedia Production
This course explores the potential of high quality interactive authoring tools to develop presentation and training systems. Programming languages within professional presentation and editing packages will be used to create systems capable of presenting graphics, animation, text, sound and music, based on the users requests. Students will learn how to define and manipulate classical techniques such as storyboarding, staging, and interactivity. The laboratory has had a large collection of computer animation, graphic, and multimedia tools, and is developing new authoring tools. During the first month and a half, the course will concentrate on state-of-the-art multimedia composition and presentation techniques and developing small individual projects. The second half of the semester will emphasize working as a group to create a single, high quality multimedia production. Prerequisite: CMPSCI 591_ Seminar - 3D Computer Animation and Digital Editing. Permission of the instructor required; contact: Beverly Woolf 545-4265. 3 credits.
CMPSCI 691M: Combinatorial Optimization
This course surveys some of the main themes in combinatorial optimization, with an emphasis on theoretical rigor, computational analysis, and applications in computer science. Topics covered include: linear programming; Karmarkar's algorithm; specialized applications of linear programming; flow algorithms; branch and bound techniques; integer programming; dynamic programming; graph algorithms; local search; simulated annealing; and a brief look at nonlinear programming. The course should be of interest both to computer science students and to mathematically sophisticated engineering students. Prerequisites: Mathematical maturity (linear algebra essential). 3 credits.
CMPSCI 691O: Seminar - Tools for Explanatory and Tutoring Systems
This seminar examines recent work in explanatory and tutoring systems. We will explore research issues in: Collaboratory Environments, Dialogue Systems, Authoring Tools, User Models. The objective of the course is to stimulate awareness of researchissues and to promote sound analytic and design skills as they pertain to building knowledge representations and control strategies. Relevant topics and applications will be presented through readings in the recent literature. Each student will prepare written critiques of each paper, lead several in-class discussions and prepare appropriate questions about the research. Several working systems will be available for hands-on critique. Readings for the course are contained in several bound volumes of articles and technical reports available in the main CMPSCI office. There is a charge for these volumes. 3 credits.
CMPSCI 691Q: Seminar - Network Support for Multicast (Group) Communications
There is tremendous demand for network support for group applications, those that involve three or more participating users. Examples of such applications include teleconferencing, distributed games, software distribution, distributed database updates,and command/control systems. This seminar will focus on the issues that arise when developing appropriate network services for these applications and the recent trends in their resolution. The most important of these issues relate to the scalability of proposed services and their suitability for applications including users with widely differing capabilities. Specifically, we will focus on the following problems that must be solved in order to provide efficient scalable support for group communications: i) routing, ii) congestion control, iii) reliable multicast. We will review different proposed routing algortihms including PIM and the core based tree approach. In the area of congestion control, we will review window- and rate-based methods inuse for ponit-point applications and identify the issues that make the problem of congestion control much more difficult in the multicast setting. We will then review several proposals including extensions to the window- and rate-based schemes along with a novel new approach, receiver layered multicasting. An important issue that we will explore regards how well group applications using multicast congestion control techniques interact with traditional point-point applications in the face of congestion. In the area of reliable multicast, we will review different approaches and their potential advantages/disadvantages. We will also consider how methods for enhancing reliability integrate with congestion control methods. Last, we will examine a number of other issues that arise including pricing, workload characterization, etc. Course Work: All students taking course will participate in discussion and will present material for one class. This can be done for no credit or one credit. Students can receive three credits if, in addition, they do a course project. 1 or 3 credits.
CMPSCI 691Z: Performance Evaluation
CMPSCI 696A: Independent Study - Computer Networks and Distributed Processing
CMPSCI 735: Advanced Computer Architecture
This course will cover advanced topics in computer architecture. These may include advanced scalar processor techniques, research parallel processing systems, nontraditional processor architectures such as dataflow and logical inference engines, and optical computing elements. Participants will be expected to read and critique a collection of recent research papers, and will work in small groups on a semester research project. 3 credits.
CMPSCI 791B: Seminar - Analyzing of Distributed and Concurrent Systems
Increasingly society's fundamental infrastructure, such as air traffic control, monetary fund transfers, and medical procedures, are being supported by software systems. Thus, the implications of software failure can be catastrophic in terms of human lives and economic loss. At the same time, with the advent of wide-scale networking, such as the world wide web, applications are increasingly being written as concurrent and/or distributed systems, even though such systems are significantly more difficult to test and validate. This course will explore the major research approaches being developed to analyze concurrent and distributed systems. In particular we will look at reachability analysis, symbolic model checking, data flow analysis, and integernecessary condition analysis. Most of these approaches attempt to verify that selected safety requirements are guaranteed to be valid for all possible executions. Unfortunately, most of these approaches have worst case bounds that are at least exponential. We will examine techniques being developed to make these approaches practical and experiment with the current tools that represent these approaches. We will also explore the issues that need to be addressed for these approaches to be applicable to Java, which poses some interesting problems. 3 credits.
CMPSCI 791M: Seminar - Garbage Collection
We will survey in depth automatic storage management techniques (popularly called garbage collection) using a recently published book and papers from the research literature. We will focus on uniprocessor techniques for programming languages but may have time to consider multiprocessor techniques, disk/database garbage collection, or distributed system techniques. Students will prepare most presentations and lead seminar discussion. Students may undertake a project in conjunction with the seminar byregistering for independent study. 1 credit.
CMPSCI 791O: Seminar - Reinforcement Learning
This course will provide a comprehensive introduction to reinforcement learning, an approach to artificial intelligence emphasizing learning from interaction to achieve goals in a stochastic and uncertain environment. Reinforcement learning has adaptedkey ideas from machine learning, operations research, control theory, psychology, and neuroscience to produce some strikingly successful engineering applications. The focus is on algorithms that learn what actions to take when so as to optimize long-term performance. This may involve sacrificing immediate reward to obtain greater reward in the long-term or just to obtain more information about the environment. The course will cover Markov decision processes, dynamic programming, temporal-difference learning, Monte Carlo methods, eligibility traces, the role of neural networks, and the integration of learning and planning. 3 credits.
CMPSCI 791Q: Seminar - Topics in Information Retrieval
This seminar covers current and recent research in Information Retrieval as well as significant results from the past. We will discuss how this research relates (or does not relate) to the work done locally. Specific topics may include probabilistic IR, visualization, passage handling, routing (feedback), query expansion, summarization, integration with databases, natural language processing, and so forth. Participants will be expected to read 1-3 papers per week (rarely more than 2). A short (halfpage) synopsis of each paper will be due before the class in which a paper is discussed. One or more attendees will be responsible for presenting a 10-15 minute summary of each paper. When possible, researchers will be asked to relate their work to the papers. Discussion of the papers will follow. A prerequisite for this seminar is CMPSCI 691I (646), the Information Retrieval course, or its equivalent. Contact James Allan (email@example.com) if you are uncertain whether you have the necessary background. 3 credits.
CMPSCI 891M: Theory of Computation
Lectures on various topics in the theory of computation by CMPSCI theory faculty, possible guest speakers, and seminar students. May be repeated for credit. Prerequisite: Graduate standing in CMPSCI or permission of the instructor. 1 credit.
CMPSCI H01: Honors Colloquium for CMPSCI 287
We will examine how the programming paradigms discussed in 287 are exhibited in more modern Functional Languages (SML, Haskell), Logic Languages (Prolog), Object Oriented Languages (C++ & the objectclass extension of Pop-11). Recommended for Juniors, Seniors. 1 credit.
CMPSCI H02: Honors Colloquium for CMPSCI 320
In this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semester-long team project in which a software development project is carried through all the stagesof the software life cycle. Honors students will be expected to assume responsibility for some of the more complex aspects as well as to study more advanced concepts. 1 credit.
CMPSCI H03: Honors Colloquium for CMPSCI 311
We study more advanced material in the theory and implementation of algorithms. Possible topics include approximate string matching, computational biology, computational geometry, cryptography, approximate solution to combinatorial optimization problems, advanced data structures, parallel algorithms, and data compression. Typically, students research an area of mutual interest, and present it to the rest of the class. 1 credit.
CMPSCI H04: Honors Colloquium for CMPSCI 491A (410)
In addition to scheduled class hours, an additional class for advanced topics will be required. The course contains a five-part programming project and the honors students will be required to complete more advanced functionality for each of the parts.1 credit.
CMPSCI H05: Honors Colloquium for CMPSCI 535
Honors students read additional materials in the area of computer architecture and meet once each week with the instructor to report on and discuss the readings. Recommended for Juniors, Seniors; Majors. 1 credit.
CMPSCI H06: Honors Colloquium for CMPSCI 520
Students will do additional readings on subjects related to synthesis of computer software artifacts, and will complete an additional project, as mutually agreed by the instructor and student. In addition, students will meet with the instructor on an individual basis as necessary and agreed upon. 1 credit.
CMPSCI H08: Honors Colloquium for CMPSCI 201
We select one or more of the course topics and explore them in more depth than is possible in the standard course. In particular, we see how the architectural concepts are applied in a real computer rather than the simple instructional computer used inclass. Readings are assigned and discussed in once-a-week meetings. Students are assigned one or more projects using an Intel I86 based computer, such as the IBM PC, that require application of the concepts studied studied in class. Grades are basedon written reports, participation in discussions, and the application of concepts in the projects. 1 credit.
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