Last spring, I taught a literature seminar called "Before Wikipedia." The subject was the history of encyclopedic writing, from ancient times to the present day. We read excerpts of Isidore of Seville's "Etymologies" and Diderot's "Encyclopédie" alongside works by Calvino, Sebald, and Flaubert. The word "Wikipedia" in the course title seemed to attract an unusual preponderance of science majors for a seminar in comparative literature. There were physicists and mathematicians, a cluster of coders, an engineer, a neuroscience major.

The first 11 teams for a race in which robot cars will jostle with real ones along mocked-up city streets have been announced. The teams must construct autonomous vehicles to navigate an unfamiliar urban environment in the shortest time possible. The robot racers will face a "simulated" urban course 96 kilometres (60 miles) in length in November 2007. The course will feature urban obstacles, such as trees and buildings, traffic signs and other moving vehicles. Its location is yet to be disclosed.

Debrief tool used in the experiment displays a video replay of the operator console (similar to this map display), and a timeline of events suggested by AEMASE for discussion during debrief. The tool also includes visualizations of entity movement over time. Navy pilots and other flight specialists soon will have a new "smart machine" installed in training simulators that learns from expert instructors to more efficiently train their students. Sandia National Laboratories' Automated Expert Modeling & Student Evaluation (AEMASE, pronounced "amaze") is being provided to the Navy as a component of flight simulators. Components are now being used to train Navy personnel to fly H-60 helicopters and a complete system will soon be delivered for training on the E-2C Hawkeye aircraft, said Robert G. Abbott, a Sandia computer scientist and AEMASE's inventor.

Soon they will be sophisticated enough to fill certain faculty roles at traditional universities. But to make this revolution work for students, academic leaders at those traditional institutions will need to broker a peace between artificially intelligent teaching programs and their human counterparts, according to a new report written by the former presidents of two prominent traditional universities on behalf of the nonprofit Ithaka S R. Online education has enabled many colleges to transition into the prevailing modern medium while adding new sources of revenue in times of scarcity, according to the Ithaka report. However, these innovative colleges have shown less interest in using the novel medium to curb tuition charges and measure learning outcomes. The report, called "Barriers to Adoption of Online Learning Systems in U.S. Higher Education," was co-written by Lawrence S. Bacow and William G. Bowen, the former presidents of Tufts and Princeton Universities, respectively, along with several Ithaka analysts. It was bankrolled by the Bill & Melinda Gates Foundation.

In his 10-week course Ng takes a an engineering-oriented approach to Machine Learning that concentrates on statistical models. If you are looking for an alternative Coursera also has Neural Networks for Machine Learning, a class taught by University of Toronto professor, Geoffry Hinton who is a leading proponent in the field from a cognitive science perspective. His eight-week course sets out to teach students artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion. Its prerequisites are programming proficiency in Matlab, Octave or Python, plus knowledge of calculus, linear algebra and probability theory.

A* algorithm tutorial Tweet Production quality source code accompanying this tutorial can be found on Github Related blog posts Who uses this A* code Bug fixes Avoiding ten common video game AI mistakes Introduction Welcome to this A* tutorial. The A* algorithm is often used in video games to enable characters to navigate the world. This tutorial will introduce you the algorithm and describe how to implement it. State space search A* is a type of search algorithm. Some problems can be solved by representing the world in the initial state, and then for each action we can perform on the world we generate states for what the world would be like if we did so. If you do this until the world is in the state that we specified as a solution, then the route from the start to this goal state is the solution to your problem. In this tutorial I will look at the use of state space search to find the shortest path between two points (pathfinding), and also to solve a simple sliding tile puzzle (the 8-puzzle).

Taking a computer science course will mean you will be studying a subject at the very forefront of technology and innovation. Computers are everywhere, and the demand to make them smaller, work more quickly, and be fitted with new and exciting software has never been greater. Most computing courses tend to focus on software engineering - things like database design, network systems, computer hardware, the internet. But there are other options in this field, such as artificial intelligence, cybernetics, and multimedia and games design, and apps design. You will be expected to be good at maths and an interest in physics would also help, as most of the theory will touch on both subjects.

Anant Agarwal is a professor of electrical engineering and computer science at the Massachusetts Institute of Technology and president of edX, a leading provider of massive open online courses, known as Moocs. Created by the Massachusetts Institute of Technology and Harvard, edX is a non-profit, "open-source" organisation. Everybody should have access to a high-quality education. At edX we are applying technology to improve education in quality, scale and accessibility. We have about 1m people enrolled in edX.

To the list of French accomplishments you may now add "robot basketball training" -- at least if the video above is to be believed. But you probably shouldn't believe it when members of Poitiers Basket 86 testify that amusement park rides improved the team's "spatial orientation" and helped them defeat top-ranked Chalon. It'd be different if the "robots" were teaching them perfect free-throw or helping them walk, obviously, but PB86 is known for its innovative advertising, and this seems like a quirky example. Hit the video above to see the pranksters at work, but know that, as with Sartre and Camus, something gets lost in translation.