This module provides an introduction to artificial neural nets with a working network that can solve X-OR problem.
Chain codes are a kind of computer program that can be used to represent the shape of objects. Seven hands-on activities show how to write simple chain codes and explain their application to computer vision.
The physics-based simulator, Breve, is used to introduce complex adaptive systems with a special focus on the optimization strategy known as simulated annealing .
Computers play a central role in artificial intelligence, robotics, and in modeling various capabilities of minds/brains. But what is a computer? Are all computers the same? This module answers these questions.
Neurons form elaborate information processing networks. Connectionist networks (or artificial neural nets) are special computer programs that simulate those networks. This module explains how connectionist networks work.
Larry Learner is an artificial intelligence program that plays the game "Last One Loses." There are two versions of Larry -- one version is programmed to win. Another version doesn't know how to win, at first, but it learns.
McCulloch and Pitts developed a mathematical model of a biological neuron. Learn about the original MCP neuron as well as further developments that would eventually lay the foundation for today's connectionist networks (artificial neural nets).
This is a comprehensive introduction to robotics that focuses on the use of robotics in medicine and that features three stand-alone virtual robotics labs one "top-down" lab and two behavior-based or "bottom-up" labs.
The computer processing in virtually all robots is digital. What significant differences would there be in a robot that was controlled by an analog, water computer? Compare two robots which behave the same but one is digital, one is analog.
This module leads students through the construction of simple Turing machines, through universal machines, and finally onto a 'natural language' machine that can parse simple English sentences.
You build a "top-down", write scripts to control its motors, and train its AI software so that it will perform interesting tasks. After creating the virtual robot, join the Mind Project Team and build a physical version of the same Iris.4 robot.
With videos of actual robots, users are able to experiment with thousands of different programming combinations ("hierarchies") to solve a robotic-design challenge in behavior-based robotics.
Students become field anthropologists and conduct a study on cultural differences in the use of color terms. Students learn current research methods and struggle with the long-standing dispute between universalists and relativists.
Is it possible to build a machine that is intelligent? That question is explored as users play games with Larry Learner, an AI program, and consider the significance.
Some computer scientists say that in the next 40 years we will be able to transfer our minds into a robot and live, virtually forever. In this monograph, Win Phillips examines the plausibility of this "extraordinary" claim. (Image by Nancy Stahl)
Functionalism asserts that minds and their mental states (pains, beliefs, etc.) are defined by their function (or software design) not their physical make-up (hardware). This means that machines as well as biological organisms could have minds.
John Searle's Chinese Room Argument challenges one of the most popular theories on the nature of the human mind. Many passionately defend the argument; many others viciously attack it. Come and try to understand what all the fuss is about.
An introduction to empirical knowledge, scientific reasoning, and the logic underlying the scientific method.
Alan Turing proposed a fascinating test for "machine intelligence" in 1950 which remains at the center of controversy. Offered here is a flash animation showing one way the test might be conducted and the types of questions that might be asked.
"Is it possible to build a person?" Various criteria of personhood are considered and students are challenged to develop their own criteria and to judge whether or not those properties could be “mechanized” and built into a machine.
This is an Introduction to Linguistics textbook that pays particular attention to the contributions that cognitive science makes to our understanding of language. It is remarkable that a text of this quality is free on the Internet.
This project challenges the way students think about language. Familiar concepts such as words and sentences are replaced by abstract objects that are novel and introduce new ways of thinking about semantic, phonemic and orthographic structure.
This is an online version of portions of the Steve Weisler & Slavko Milekic book Theory of Language originally published in CD-ROM and print form by MIT Press. Effective activities and many videos enhance this linguistics textbook.
This computer program learns to win at the game of "coins." It demonstrates how reinforcement learning can solve the problem of backward induction.
This project allows students to explore evolution using simple robots that attempt to solve problems such as staying alive the longest or traveling the farthest.
This project allows students to explore reinforcement learning using simple LEGOS Mindstorms robots. Students work with the robots to solve problems such as staying alive the longest or traveling the farthest.
Through reinforcement learning, this virtual world demonstrates how an organism can learn from its environment, and how learning depends on the composition of the environment and its rewards and punishments.
In this demonstration, students experiment on their own working memories to test various models that describe how the contents of memory are matched to a test item.
Neural synchrony is the simultaneous / synchronous oscillations of membrane potentials in a network of neurons connected with electrical synapses (gap junctions). It is considered by some theorists to be the neural correlate of consciousness.
An introduction to the structure and function of neurons, conduction of action potentials, synapses, and both chemical and electrical neurotransmission.
This program is a virtual EEG (electroencephalogram) lab. You will design your own experiment and "gather" data regarding how electrical activity in the brain is associated with various images.
Students in this immersive lab measure dopamine levels in rats with Parkinson's symptoms to compare competing theories which seek to solve the mystery of how the brain compensates for the death of dopamine neurons.
This program lets students explore apparent motion phenomenon and test models of mapping between objects. In the applet, apparent motion occurs when a dot disappears from one location and reappears in another location.
We form categories as part of everyday life. Sometimes this is good while sometimes they can lead to societal problems. This program allows students to explore how categories are created and how they affect our perception and judgments of images.
Change Blindness occurs when a brief flash comes between two versions of a scene. This flash prevents the change from rising to the level of a person's consciousness. This program allows users to design experiments that explore change-blindness.
There are both classical AI programs and neural networks that can process visual information about the world and give machines the ability to "see." This module explores different approaches to computer vision.
This java applet and application allow students to create lifelike artificial faces for use in memory and visual search experiments.
The Müller-Lyer Illusion is one of the most famous examples of the human visual system misinterpretting the world. Become a subject in an online Müller-Lyer experiment. Try to explain why this happens.
Human beings perceive the world through their senses. This module explores the difference between sensation and perception, the importance of perception, and how perception is studied in the cognitive and learning sciences.
Many decisions in life surround one of two possible alternatives and two possible choices. In this experiment students explore the tradeoffs that can occur when trying to detect a known signal.
This is a brief introduction to the scientific study of visual perception, featuring animations that generate visual phenomena requiring scientific analysis.
This program allows students to create their own visual search experiments to explore visual perception and memory phenomenon. Students have used this to explore effects of familiarity, search asymmetries and more.