64,955 research outputs found
Improved Reinforcement Learning with Curriculum
Humans tend to learn complex abstract concepts faster if examples are
presented in a structured manner. For instance, when learning how to play a
board game, usually one of the first concepts learned is how the game ends,
i.e. the actions that lead to a terminal state (win, lose or draw). The
advantage of learning end-games first is that once the actions which lead to a
terminal state are understood, it becomes possible to incrementally learn the
consequences of actions that are further away from a terminal state - we call
this an end-game-first curriculum. Currently the state-of-the-art machine
learning player for general board games, AlphaZero by Google DeepMind, does not
employ a structured training curriculum; instead learning from the entire game
at all times. By employing an end-game-first training curriculum to train an
AlphaZero inspired player, we empirically show that the rate of learning of an
artificial player can be improved during the early stages of training when
compared to a player not using a training curriculum.Comment: Draft prior to submission to IEEE Trans on Games. Changed paper
slightl
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Knowledge Cartography: Software tools and mapping techniques
Knowledge Cartography is the discipline of mapping intellectual landscapes.The focus of this book is on the process by which manually crafting interactive, hypertextual maps clarifies one’s own understanding, as well as communicating it.The authors see mapping software as a set of visual tools for reading and writing in a networked age. In an information ocean, the primary challenge is to find meaningful patterns around which we can weave plausible narratives. Maps of concepts, discussions and arguments make the connections between ideas tangible and disputable.
With 17 chapters from the leading researchers and practitioners, the reader will find the current state–of-the-art in the field. Part 1 focuses on educational applications in schools and universities, before Part 2 turns to applications in professional communitie
Challenging the Computational Metaphor: Implications for How We Think
This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think
Evaluation and assessment of professional skills in the Final Year Project
In this paper, we present a methodology for Final Year Project (FYP) monitoring and assessment that considers the inclusion of the professional skills required in the particular engineering degree. This proper monitoring and clear evaluation framework provides the student with valuable support for the project implementation as well as for improving the quality of the projects, thereby reducing the academic drop-out rate. The proposed methodology has been implemented at the Barcelona School of Informatics at the Universitat Politècnica de Catalunya - BarcelonaTech. The FYP is structured around three milestones: project definition, project monitoring and project completion.
Skills are assigned to each milestone according to the tasks required in that phase, and a list of indicators is defined for each phase. The evaluation criteria for each indicator at each phase are specified in a rubric, and are made public both to students and teachers. Thus, the FYP includes an exhaustive evaluation method distributed throughout the whole project implementation, thereby facilitating project organization for the student as well as providing a clear and homogeneous assessment framework. The methodology for the FYP organization, assessment and evaluation was launched and piloted over two semesters. We believe the experience to be general in the sense that it has been conducted as part of an ICT engineering degree, but may easily be extended to any other engineering degree.Postprint (author’s final draft
Web Science: expanding the notion of Computer Science
Academic disciplines which practice in the context of rapid external change face particular problems when seeking to maintain timely, current and relevant teaching programs. In different institutions faculty will tune and update individual component courses while more radical revisions are typically departmental-wide strategic responses to perceived needs. Internationally, the ACM has sought to define curriculum recommendations since the 1960s and recognizes the diversity of the computing disciplines with its 2005 overview volume. The consequent rolling program of revisions is demanding in terms of time and effort, but an inevitable response to the change inherent is our family of specialisms. Preparation for the Computer Curricula 2013 is underway, so it seems appropriate to ask what place Web Science will have in the curriculum landscape. Web Science has been variously described; the most concise definition being the ‘science of decentralized information systems’. Web science is fundamentally interdisciplinary encompassing the study of the technologies and engineering which constitute the Web, alongside emerging associated human, social and organizational practices. Furthermore, to date little teaching of Web Science is at undergraduate level. Some questions emerge - is Web Science a transient artifact? Can Web Science claim a place in the ACM family, Is Web Science an exotic relative with a home elsewhere? This paper discusses the role and place of Web Science in the context of the computing disciplines. It provides an account of work which has been established towards defining an initial curriculum for Web Science with plans for future developments utilizing novel methods to support and elaborate curriculum definition and review. The findings of a desk survey of existing related curriculum recommendations are presented. The paper concludes with recommendations for future activities which may help us determine whether we should expand the notion of computer science
Product Focused Freeform Fabrication Education
Presented in this paper is our experience of teaching freeform fabrication to students at
the Missouri University of Science and Technology, and to high school students and
teachers. The emphasis of the curriculum is exposing students to rapid product
development technologies with the goal of creating awareness to emerging career
opportunities in CAD/CAM. Starting from solid modeling, principles of freeform
fabrication, to applications of rapid prototyping and manufacturing in industry sponsored
product development projects, students can learn in-depth freeform fabrication
technologies. Interactive course content with hands-on experience for product
development is the key towards the success of the program.Mechanical Engineerin
Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences
This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering
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