This course will present advanced topics in Artificial Intelligence (AI), including inquiries into logic, artificial neural network and machine learning, and the Turing machine. Upon successful completion of this course, students will be able to: define the term 'intelligent agent,' list major problems in AI, and identify the major approaches to AI; translate problems into graphs and encode the procedures that search the solutions with the graph data structures; explain the differences between various types of logic and basic statistical tools used in AI; list the different types of learning algorithms and explain why they are different; list the most common methods of statistical learning and classification and explain the basic differences between them; describe the components of Turing machine; name the most important propositions in the philosophy of AI; list the major issues pertaining to the creation of machine consciousness; design a reasonable software agent with java code. (Computer Science 408)

This course is an investigation of affective priming and creation of rigorously counterbalanced, fully computerized testing paradigm. Includes background readings, study design, counterbalancing, study execution, data analysis, presentation of poster, and final paper.

Survey of principles underlying the structure and function of the nervous system, integrating molecular, cellular, and systems approaches. Topics: development of the nervous system and its connections, cell biology or neurons, neurotransmitters and synaptic transmission, sensory systems of the brain, the neuroendocrine system, the motor system, higher cortical functions, behavioral and cellular analyses of learning and memory. First half of an intensive two-term survey of brain and behavioral studies for first-year graduate students. Open to graduate students in other departments, with permission of instructor.

This class is the second half of an intensive survey of cognitive science for first-year graduate students. Topics include visual perception, language, memory, cognitive architecture, learning, reasoning, decision-making, and cognitive development. Topics covered are from behavioral, computational, and neural perspectives.

This course is designed to provide an understanding of how the human brain works in health and disease, and is intended for both the Brain and Cognitive Science major and the non-Brain and Cognitive Science major. Knowledge of how the human brain works is important for all citizens, and the lessons to be learned have enormous implications for public policy makers and educators. The course will cover the regional anatomy of the brain and provide an introduction to the cellular function of neurons, synapses and neurotransmitters. Commonly used drugs that alter brain function can be understood through a knowledge of neurotransmitters. Along similar lines, common diseases that illustrate normal brain function will be discussed. Experimental animal studies that reveal how the brain works will be reviewed. Throughout the seminar we will discuss clinical cases from Dr. Byrne's experience that illustrate brain function; in addition, articles from the scientific literature will be discussed at each class.

An introduction to human information processing and learning; topics include the nature of mental representation and processing; the architecture of memory; pattern recognition; attention; imagery and mental codes; concepts and prototypes; reasoning and problem solving.

Used for students receiving Advanced Placement credit and transfer credit. Program of study or research to be arranged with a Department faculty member. Written report required. Permission of Department required.

Basic principles of learning are always operating and always influencing human behavior. This module discusses the two most fundamental forms of learning -- classical (Pavlovian) and instrumental (operant) conditioning. Through them, we respectively learn to associate 1) stimuli in the environment, or 2) our own behaviors, with significant events, such as rewards and punishments. The two types of learning have been intensively studied because they have powerful effects on behavior, and because they provide methods that allow scientists to analyze learning processes rigorously. This module describes some of the most important things you need to know about classical and instrumental conditioning, and it illustrates some of the many ways they help us understand normal and disordered behavior in humans. The module concludes by introducing the concept of observational learning, which is a form of learning that is largely distinct from classical and operant conditioning.

This textbook presents core concepts common to introductory courses. The 15 units cover the traditional areas of intro-to-psychology; ranging from biological aspects of psychology to psychological disorders to social psychology. This book can be modified: feel free to add or remove modules to better suit your specific needs.

This book includes a comprehensive instructor's manual, PowerPoint presentations, a test bank, reading anticipation guides, and adaptive student quizzes.

Surveys the literature on the cognitive and neural organization of human memory and learning. Includes consideration of working memory and executive control, episodic and semantic memory, and implicit forms of memory. Emphasizes integration of cognitive theory with recent insights from functional neuroimaging (e.g., fMRI and PET). Alternate years.

To be information literate, a person must be able to recognize when information is needed and have the ability to locate, evaluate, and use effectively the needed information. By the end of this unit you will be able to Define Information Literacy, Define the four domains that fall under Metaliterate Learners, Identify a lack of knowledge in a subject area, Identify a search topic/question and define it using simple terminology, Articulate current knowledge on a topic, Recognize a need for information and data to achieve a specific end and define limits to the information need, and Manage time effectively to complete a search.

Organization of synaptic connectivity as the basis of neural computation and learning. Single and multilayer perceptrons. Dynamical theories of recurrent networks: amplifiers, attractors, and hybrid computation. Backpropagation and Hebbian learning. Models of perception, motor control, memory, and neural development. Alternate years.

" This course is an introduction to the mammalian nervous system, with emphasis on the structure and function of the human brain. Topics include the function of nerve cells, sensory systems, control of movement, learning and memory, and diseases of the brain."

When you teach Introduction to Psychology, do you find it difficult — much harder than teaching classes in statistics or research methods? Do you easily give a lecture on the sympathetic nervous system, a lecture on Piaget, and a lecture on social cognition, but struggle with linking these topics together for the student? Do you feel like you are presenting a laundry list of research findings rather than an integrated set of principles and knowledge? Have you wondered how to ensure your course is relevant to your students? Introduction to Psychology utilizes the dual theme of behavior and empiricism to make psychology relevant to intro students. The author wrote this book to help students organize their thinking about psychology at a conceptual level. Five or ten years from now, he does not expect his students to remember the details of most of what he teaches them. However, he does hope that they will remember that psychology matters because it helps us understand behavior and that our knowledge of psychology is based on empirical study.

This is a derivative of INTRODUCTION TO PSYCHOLOGY by a publisher who has requested that they and the original author not receive attribution, which was originally released and is used under CC BY-NC-SA. This work, unless otherwise expressly stated, is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

This course is a survey of the scientific study of human nature, including how the mind works, and how the brain supports the mind. Topics include the mental and neural bases of perception, emotion, learning, memory, cognition, child development, personality, psychopathology, and social interaction. Students will consider how such knowledge relates to debates about nature and nurture, free will, consciousness, human differences, self, and society.

During the early days of the pandemic, Dr. Gina Rae Foster, Teaching & Learning Center Director at John Jay College of Criminal Justice wrote a series of emails to faculty to support and guide instructors in helping their students and in redesigning their courses in the midst of lockdowns and racial violence. This guide is intended to address multiple interests and needs: as an informal and partial teaching guide, as an edited historical artifact, as a developing set of perspectives on social justice, and as a reminder that our individual and collective wellbeing can be reciprocal and can be amplified.

This experience-based course will develop multicultural counseling competence, specifically awareness, knowledge, and skill related to cultural, racial, linguistic, ethnic, gender, sexual identity, age, ability, and socioeconomic factors that influence and shape behavior and development, including privilege and oppression in each of these areas. There is an emphasis on intersectionality. Personal history, literature, and films will be analyzed in the contexts of acculturation, identity, and systemic oppression. Current research and theoretical and applied knowledge in this field will be reviewed. Students will integrate theoretical and applied knowledge in written assignments and discussions.

The course focuses on the problem of supervised learning within the framework of Statistical Learning Theory. It starts with a review of classical statistical techniques, including Regularization Theory in RKHS for multivariate function approximation from sparse data. Next, VC theory is discussed in detail and used to justify classification and regression techniques such as Regularization Networks and Support Vector Machines. Selected topics such as boosting, feature selection and multiclass classification will complete the theory part of the course. During the course we will examine applications of several learning techniques in areas such as computer vision, computer graphics, database search and time-series analysis and prediction. We will briefly discuss implications of learning theories for how the brain may learn from experience, focusing on the neurobiology of object recognition. We plan to emphasize hands-on applications and exercises, paralleling the rapidly increasing practical uses of the techniques described in the subject.

This course highlights the interplay between cellular and molecular storage mechanisms and the cognitive neuroscience of memory, with an emphasis on human and animal models of hippocampal mechanisms and function. Class sessions include lectures and discussion of papers.

Roles of neural plasticity in learning and memory and in development of invertebrates and mammals. An in-depth critical analysis of current literature of molecular, cellular, genetic, electrophysiological, and behavioral studies. Discussion of original papers supplemented by introductory lectures.