Fall 2010: CSCI-445 Introduction to Robotics

The objective of this course is to use a hands-on approach to introduce concepts in robotics, focusing on mobile robots and illustrations of state of the art research. Students work in teams to build and test increasingly complex mobile robots, culminating in a robot contest. Topics covered include the historical development of robotics, sensors, effectors, control (reactive, behavior-based, and hybrid), integration, robot learning, and multi-robot systems.

Fall 2010: CSCI-561 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Fall 2009: CSCI-445 Introduction to Robotics

The objective of this course is to use a hands-on approach to introduce concepts in robotics, focusing on mobile robots and illustrations of state of the art research. Students work in teams to build and test increasingly complex mobile robots, culminating in a robot contest. Topics covered include the historical development of robotics, sensors, effectors, control (reactive, behavior-based, and hybrid), integration, robot learning, and multi-robot systems.

Fall 2009: CSCI-460 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Fall 2008: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Fall 2008: CSCI-445 Introduction to Robotics

The objective of this course is to use a hands-on approach to introduce concepts in robotics, focusing on mobile robots and illustrations of state of the art research. Students work in teams to build and test increasingly complex mobile robots, culminating in a robot contest. Topics covered include the historical development of robotics, sensors, effectors, control (reactive, behavior-based, and hybrid), integration, robot learning, and multi-robot systems.

Fall 2008: CSCI-460 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Spring 2008: CSCI-445 Introduction to Robotics

The objective of this course is to use a hands-on approach to introduce concepts in robotics, focusing on mobile robots and illustrations of state of the art research. Students work in teams to build and test increasingly complex mobile robots, culminating in a robot contest. Topics covered include the historical development of robotics, sensors, effectors, control (reactive, behavior-based, and hybrid), integration, robot learning, and multi-robot systems.

Spring 2008: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Fall 2007: CSCI-561 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Fall 2007: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Fall 2006: CSCI-445 Introduction to Robotics

The objective of this course is to use a hands-on approach to introduce concepts in robotics, focusing on mobile robots and illustrations of state of the art research. Students work in teams to build and test increasingly complex mobile robots, culminating in a robot contest. Topics covered include the historical development of robotics, sensors, effectors, control (reactive, behavior-based, and hybrid), integration, robot learning, and multi-robot systems.

Spring 2006: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Spring 2006: CSCI-561 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Fall 2005: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Fall 2005: CSCI-460 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Spring 2005: CSCI-561 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Spring 2005: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Fall 2004: CSCI-599 Computational Architectures in Biological Vision

This course will review a number of computational architectures found in biological vision systems and challenging artificial vision systems, such as the computation of depth from two retinal images, the computation of motion from optic flow, mechanisms for orienting and visual attention, the analysis of complex cluttered scenes, and the recognition of complex objects. For each of these problems (and many others; see syllabus below) the major computational issues will be analyzed. A critical comparison will then be carried between biological implementations and engineering implementations derived from signal processing and computer vision.

The overall goal of this course is to provide students with an understanting of the major computational issues in vision and a critical overview of the latest advances in both computer vision and visual neuroscience. As some of the most successful computer vision algorithms today have direct biological inspiration, it has become essential for the engineer and scientist of tomorrow to have a broad understanding of the major computational architectures found in biological vision. This course will provide background, introductory material to familiarize the student with the major challenges in computer and biological vision. It will then critically compare the approaches employed by both fields, and survey how, in many cases, the interplay between both types of approaches has resulted in some of the most powerful artificial vision systems to date.

Applications studied in class will include the evaluation of web designs (to create web pages that are easy to use and navigate, based on the properties of the human visual system), the design of efficient advertising (either in conventional or WWW media), robot vision, the efficient compression of streaming video based on the properties of the visual system, embarked navigation aids, etc.

Fall 2004: CSCI-460 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Fall 2004: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Spring 2004: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Fall 2003: CSCI-561 Artificial Intelligence

This course introduces the basic concepts and methods used in Artificial Intelligence research, including agents, search, problem solving, representation, reasoning and symbolic programming. Please see the class home page for a complete description and syllabus.

Fall 2003: CSCI-460 Artificial Intelligence

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks. Please see the class home page for a complete description and syllabus.

Fall 2003: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Spring 2003: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Fall 2002: CSCI-561 Artificial Intelligence

This course introduces the basic concepts and methods used in Artificial Intelligence research, including agents, search, problem solving, representation, reasoning and symbolic programming. Please see the class home page for a complete description and syllabus.

Fall 2002: CSCI-564 Brain Theory and Artificial Intelligence

This course provides a basic understanding of brain function, of the artificial neural networks which provide tools for a new paradigm for adaptive parallel computation. No background in neuroscience is required, nor is specific programming expertise, but knowledge of C++ and Linux will enable students to develop new neuromorphic vision algorithms on the Beobot platform, if they wish to, as part of their class project assignments.

Fall 2002: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Spring 2002: CSCI-664 Neural Models for Visually Guided Behavior

This course reviews neural mechanisms of visuo-motor coordination, and methods for constructing models of these mechanisms. Topics include locomotion, cognitive maps, looking, reaching and grasping. Please see web page for additional details.

Spring 2002: CSCI-597 Seminar in Computer Science Research

This course provides a series of expository lectures to introduce Ph.D. students to the breadth of research topics in CS (and, to some extent, beyond). The idea is to cycle through the subareas of USC research in CS each semester.

First-year Ph.D. Students are required to enroll for 1 unit of CSCI 597 for the first 2 semesters of the Ph.D. Program. (Applicable only to students enrolling in Summer of 2000 or later.)

Fall 2001: CSCI-561a Artificial Intelligence

This course introduces the basic concepts and methods used in Artificial Intelligence research, including agents, search, problem solving, representation, reasoning and symbolic programming. Please see the class home page for a complete description and syllabus.

Spring 2001: CSCI-599 Computational Architectures in Biological Vision

This course will review a number of computational architectures found in biological vision systems and challenging artificial vision systems, such as the computation of depth from two retinal images, the computation of motion from optic flow, mechanisms for orienting and visual attention, the analysis of complex cluttered scenes, and the recognition of complex objects. For each of these problems (and many others; see syllabus below) the major computational issues will be analyzed. A critical comparison will then be carried between biological implementations and engineering implementations derived from signal processing and computer vision.

The overall goal of this course is to provide students with an understanting of the major computational issues in vision and a critical overview of the latest advances in both computer vision and visual neuroscience. As some of the most successful computer vision algorithms today have direct biological inspiration, it has become essential for the engineer and scientist of tomorrow to have a broad understanding of the major computational architectures found in biological vision. This course will provide background, introductory material to familiarize the student with the major challenges in computer and biological vision. It will then critically compare the approaches employed by both fields, and survey how, in many cases, the interplay between both types of approaches has resulted in some of the most powerful artificial vision systems to date.

Applications studied in class will include the evaluation of web designs (to create web pages that are easy to use and navigate, based on the properties of the human visual system), the design of efficient advertising (either in conventional or WWW media), robot vision, the efficient compression of streaming video based on the properties of the visual system, embarked navigation aids, etc.

Fall 2000: CSCI-564 Brain Theory and Artificial Intelligence

This course provides a basic understanding of brain function, of the artificial neural networks which provide tools for a new paradigm for adaptive parallel computation, and of the Neural Simulation Language NSLJ which allows us to study biological and artificial neural networks ingreat detail. No background in neuroscience is required, nor is specific programming expertise, but knowledge of Java will enable students to extend the NSLJ functionality in interesting ways.