Cognitive Systems - Ανοικτό Πανεπιστήμιο Κύπρου - Open University of Cyprus
Monday, 21 October 2019 10:07

COS625: Cognitive Chips (CS, Systems)

The demands of Cognitive Computing applications are quite different from other applications. In this course we will discuss the different issues related with the hardware support for Cognitive Computing. We will start with analyzing the demands on the hardware of cognitive computing algorithms. We will present some existing workloads, libraries, and benchmarks that can be used to evaluate different systems that are going to be used for cognitive computing. We will then discuss the tradeoffs between using general purpose, reconfigurable, or dedicated hardware to perform the computations. We will introduce some examples of Bio-Inspired designs (e.g. IBM TrueNorth, UMan SpiNNaker) as to show the trends in dedicated hardware for Cognitive Computing.
Published in Cognitive Systems
Monday, 21 October 2019 10:06

COS624: Topics in Data Science

The broad availability of data in every aspect of life has created an unprecedented interest in methods for extracting useful information and knowledge from data, which is the realm of Data Science. Data Science is a very hot and very active subject in the curricula of both graduate and undergraduate studies in Universities and Colleges throughout the world these days. Even though it is not a genuinely new domain of study per se, just recently acquired a new potential to rejuvenate and homogenize some more traditional domains of study with roots in intelligence, cognition and learning like Data Mining, Machine Learning, Knowledge Discovery in Databases, Pattern Recognition etc. In this course we will delve into the foundations and principles that underlie the techniques for extracting useful knowledge from data and we will illustrate each of these concepts with one or more data mining techniques that embodies these principles. One of the primary goals of this module is to help the students view real life problems from a data perspective and learn to apply a data analytic way in solving these problems systematically. This data analytic thinking will enable prospective data science professionals to develop intuition as to how and where to apply creativity and domain knowledge to the analysis of relevant problems. Hands on knowledge and experience will be acquired in this course through the exposure to various programming assignments and projects.

Published in Cognitive Systems
This course covers the methodology of designing cognitive systems through a historical overview of the field, the review of cognitive architectures, and the hands-on experimentation with cognitive architecture platforms. It considers the environment within which the system will operate, and discusses how to represent the salient features of that environment. It continues to investigate how the cognitive system interacts with the environment, specifying the characteristics of the sensors and actuators of the system. It investigates how to represent information internally in the system, and how to analyze the characteristics that this representation should have in terms of accessibility, scalability, persistence of the information. It then examines the processes internal to cognitive system that operate on the information, and analyzes the processes of learning and reasoning in terms of their desired behaviors, the guarantees they should offer, and their interaction. It concludes by considering ways to evaluate the performance of a cognitive system, and the process of error analysis for debugging and improving its performance.
Published in Cognitive Systems
The course examines the neural processes that underlie cognitive functions, such as attention, perception, and memory. It introduces basic neuroanatomy and modern methods and techniques (e.g., functional imaging, electrophysiology) that are used by scientists to draw inferences about cognition in the normal and abnormal brain.
Published in Cognitive Systems
This course will provide students with theoretical knowledge and practical skills for designing computerized experiments for behavioral research. The course will start by providing an in-depth analysis of experimental methodology and design. It will then proceed to provide students, by means of assignments, with hands-on experience in designing experiments, collecting data from human participants, analyzing and reporting the data, and interpreting statistical results. Through this course students are expected to acquire all the necessary knowledge on how to investigate scientifically research questions of interest.
Published in Cognitive Systems
This interdisciplinary course aims to underline the importance of incorporating human factors in the design and development of adaptive interaction systems. Incorporating cognitive and emotional human factors into adaptive applications and processes enhances the user experience, usability and satisfaction while users interacting with hypermedia environments. Main thematic areas emphasize upon the convergence of psychological theories and contemporary research on computer-mediated information processing. It will initially cover topics in the field of cognitive psychology, to the extent that there is an analogy with hypermedia information; on psychological issues with regards to the role of cognitive processing and emotions on information assimilation and learning performance capabilities; on emotional intelligence within the context of Web-based interaction, etc. At a second level, topics on personalization; adaptivity; user modelling; multi-modal interactions; task and user analysis; (adaptive) user interface design principles; user interface evaluation and usability testing; will be covered, to support the adaptation issue in various application levels.
Published in Cognitive Systems
This course studies the development of cognitive agents with computational models of argumentation as the underlying foundation for cognitive human reasoning. It brings together elements from argumentation theory in AI with cognitive psychology of reasoning to study a new form of symbolic representation and reasoning that reflects cognitive reasoning processes in humans, which leads to a new style of cognitive programming for cognitive systems. Specific elements that are covered include: The logical nature of human reasoning — argumentative decision making. Argumentation theory and Argumentation Logic in CS. Conditional human logic and argumentation logic. Cognitive reasoning about actions and change. Cognitive Knowledge Representation of common sense world knowledge and Cognitive Programming. Explanation, justification and persuasion through human-system argumentative dialogues. Argumentation-based agent architectures for adaptive agents. Application of cognitive agents to personalized and adaptive recommender systems and to elements of story comprehension.
Published in Cognitive Systems
Reasoning is the foremost human intellectual ability, an ability that underlies the characterization of humans as rational animals. Reasoning critically involves the drawing inferences; on the basis of a few beliefs or premises that are either accepted or function as working hypotheses, one draws some other beliefs, the conclusions of the inference, which differ from the premises. A primary aim of this course is to introduce the students to the basic kinds of reasoning. A second aim is to present the various forms of representations on which reasoning is based. A third aim, which draws from the discussion in the two previous aims, is to examine the ways in which the form of the representational medium interacts with reasoning abilities in a variety of contexts.
Published in Cognitive Systems
Monday, 21 October 2019 09:57

COS611: Cognitive Modelling (CP, Reasoning)

The aim of this course is to provide the foundation for the computational modeling of cognition. Using a symbolic cognitive architecture we will simulate findings from a variety of popular cognitive tasks reported in the literature of attention, memory, and problem solving. Throughout the course students will learn the fundamentals of cognitive modeling and gain hands-on experience in developing their own models.
Published in Cognitive Systems
This course introduces students to state-of-the-art research on the human language faculty. The road to be traveled will take us to the more biologically oriented area of cognitive science with a fair bit of philosophy of language, from Cartesian philosophy and the mind/brain distinction all the way to the 21st century reappraisal of Darwin’s evolutionary theory, evo–devo, and genetics in relation to (human) language. The lectures will also introduce specific studies on language acquisition and impairment, from different angles, thereby including psycho- and neurolinguistic aspects of human language. The true focus of the course is thus an introduction to the challenge posed by interdisciplinarity: How can findings of theoretical linguistics be integrated with the rest of cognitive science — and indeed with biology, or the natural sciences at large? Although generative grammarians have always advocated a cognitive science perspective, in practice few concrete attempts have been made at genuine collaboration.
Published in Cognitive Systems
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