The Teachable Agents Project combines research from computer science, psychology, and education to develop computer-based learning environments. These environments utilize animated pedagogical agents to facilitate science learning and the development of self-regulated learning skills. The use of animated agents allows us to extend the cognitive scaffolding provided by various computer tools and representations (e.g., searchable text, simulations, concept maps, etc.) by embedding them in productive and motivating social-constructive interactions (e.g., peer teaching, collaboration, and assessment). Current projects include Betty's Brain, a learning-by-teaching environment for science learning; CTSiM, an environment for understanding science through a computational thinking framework; SimSelf, a relatively new project that focuses on teaching students about self-regulation and metacognition in the context of science learning; and C3STEM, a community-situated, challenge-based, collaborative STEM learning environment. Our learning environments also include extensive logging of students' interactions with the system and agents.

Project Summary: This project explores the use of qualitative physics to provide capabilities for intelligent agents. Understanding and using common sense reasoning about the physical world is a necessary prerequisite to creating many kinds of useful intelligent agents that collaborate with human partners to accomplish tasks. Examples of such tasks include damage control assessment, operations planning, sifting through on-line information for relevant data, teaching and tutoring, and developing complex scientific and engineering models. Our vehicle for these investigations is the creation of an experimental prototype, an Explanation Agent that accumulates explanations of how engineered systems work, and that uses this accumulated knowledge to answer questions and interactively formulate task-specific models of those systems.

What do flocks of birds, traffic jams, fads, drinking games, forest fires and residential segregation have in common? The answer could come from a new computational research method called agent-based modeling. Michael Macy, a sociologist at Cornell University, Ithaca, N.Y., is using this powerful new tool to look for elementary principles of self-organization that might shed new light on long-standing puzzles about how humans interact. A professor and chair of Cornell's Department of Sociology, Macy will speak Feb. 14 at the annual meeting of the American Association for the Advancement of Science in Denver in a symposium, "Artificial Agent Societies: A Computational Future for the Social Sciences." The Cornell sociologist begins his lecture with a flock of computer-generated birds wheeling synchronously through aerobatic maneuvers.

For the final project you have the option of a programming-oriented or a research-oriented final project. Whichever project you decide to do you must first meet with me to get it approved. Programming Project Choose a paper from the AAMAS proceedings (see also my AAMAS 2012 local copy, because their website is down a lot) and implement the algorithm they describe. In many cases you will need to make some simplifying assumptions. The papers discuss in class are especially good choices.

The captain s mission: To obtain information about the local medical facilities. On the computer screen in front of me, an animated Army captain is attempting to speak with an Iraqi hospital receptionist. This is a fictional scenario in a state-of-the-art military training game. On the other side of the virtual room, the receptionist listens politely as the captain explains that he has come with supplies and he would like to speak to the hospital director. The receptionist seems to hesitate, but then responds that he will be happy to assist.

Technological advancements have been rapidly evolving in recent years. Top on the list of the most beneficial technologies are wireless devices such as Wi-Fi and Bluetooth among others. Besides the obvious advantage of freedom from laborious wires, wireless technology means you no longer have to worry about costly aspects such as rewiring when the need to redesign the office space arises. Granted, it is generally accepted that due to the expenses that are associated with installation of the wireless technological systems, many people are still reluctant to switch to the wireless network in favor of the traditional cables, but when long term benefits such as productivity and efficiency are put into consideration, wireless technology is the way to go. Let's therefore have a look at the benefits pinned to wireless technology especially from a business point of view.

Our idea of setting a traffic light is as follows. Suppose there are a number of cars with their destination address standing before a crossing. All cars communicate to the traffic light their specific place in the queue and their destination address. Now the traffic light has to decide which option (ie, which lanes are to be put on green) is optimal to minimize the long-term average waiting time until all cars have arrived at their destination address. The learning traffic light controllers solve this problem by estimating how long it would take for a car to arrive at its destination address (for which the car may need to pass many different traffic lights) when currently the light would be put on green, and how long it would take if the light would be put on red.

Artificial Intelligence (AI) techniques are now being used by the practicing engineer to solve a whole range of hitherto intractable problems. This journal provides an international forum for rapid publication of work describing the practical application of AI methods in all branches of engineering. Engineering Applications of Artificial Intelligence publishes: • Survey papers/tutorials.

Expert Systems With Applications is a refereed international journal whose focus is on exchanging information relating to expert and intelligent systems applied in industry, government, and universities worldwide. The thrust of the journal is to publish papers dealing with the design, development, testing, implementation, and/or management of expert and intelligent systems, and also to provide practical guidelines in the development and management of these systems. The journal will publish papers in expert and intelligent systems technology and application in the areas of, but not limited to: finance, accounting, engineering, marketing, auditing, law, procurement and contracting, project management, risk assessment, information management, information retrieval, crisis management, stock trading, strategic management, network management, telecommunications, space education, intelligent front ends, intelligent database management systems, medicine, chemistry, human resources management, human capital, business, production management, archaeology, economics, energy, and defense. Papers in multi-agent systems, knowledge management, neural networks, knowledge discovery, data and text mining, multimedia mining, and genetic algorithms will also be published in the journal. Please click here for more information on our author services.

THEY certainly cannot be faulted for a lack of ambition. The scientists and engineers who gathered this week in Oxford for the first International Workshop on Complex Agent-Based Dynamic Networks are seeking to explain much of the world's behaviour through the use of "agents". In this context, an agent is a program that acts in a self-interested manner in its dealings with numerous other agents inside a computer. This arrangement can mimic almost any interactive system: a stockmarket; a habitat; even a business supply-chain. If the constituent parts can be understood, the reasoning goes, some insight into the whole will follow.