Summer calendar of AI-related events.

What are the central issues of CAMD by robots and animals? What does neuroscience tell us about mental development? What computational studies for mental development are needed in neuroscience and psychology? How does a robot chine learning have fruitfully been develop its cognitive and behavioral the budding research area that informed by models of human learning. For example, developmental differ fundamentally from human real physical environment.

To a forum for Ph.D. students to discuss Many of you have been receiving the evaluate submitted proposals more effectively, research and career interests.

The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is mainly due to its fast convergence speed, which is considered to be optimal in practice. In this paper, RLS methods are used to solve reinforcement learning problems, where two new reinforcement learning algorithms using linear value function approximators are proposed and analyzed. The two algorithms are called RLS-TD(lambda) and Fast-AHC (Fast Adaptive Heuristic Critic), respectively. RLS-TD(lambda) can be viewed as the extension of RLS-TD(0) from lambda=0 to general lambda within interval [0,1], so it is a multi-step temporal-difference (TD) learning algorithm using RLS methods. The convergence with probability one and the limit of convergence of RLS-TD(lambda) are proved for ergodic Markov chains. Compared to the existing LS-TD(lambda) algorithm, RLS-TD(lambda) has advantages in computation and is more suitable for online learning. The effectiveness of RLS-TD(lambda) is analyzed and verified by learning prediction experiments of Markov chains with a wide range of parameter settings. The Fast-AHC algorithm is derived by applying the proposed RLS-TD(lambda) algorithm in the critic network of the adaptive heuristic critic method. Unlike conventional AHC algorithm, Fast-AHC makes use of RLS methods to improve the learning-prediction efficiency in the critic. Learning control experiments of the cart-pole balancing and the acrobot swing-up problems are conducted to compare the data efficiency of Fast-AHC with conventional AHC. From the experimental results, it is shown that the data efficiency of learning control can also be improved by using RLS methods in the learning-prediction process of the critic. The performance of Fast-AHC is also compared with that of the AHC method using LS-TD(lambda). Furthermore, it is demonstrated in the experiments that different initial values of the variance matrix in RLS-TD(lambda) are required to get better performance not only in learning prediction but also in learning control. The experimental results are analyzed based on the existing theoretical work on the transient phase of forgetting factor RLS methods.

Botball is a national program in which teams of middle and high school students design, build, and program small autonomous mobile robots to compete in a highly charged interactive (but nondestructive) tournament. Botball students learn to program in c, construct feedback and control loops, create electromechanical systems, and integrate it all together while they work on a team. Botball takes place in regional tournaments across the country and culminates in a National Botball Tournament traditionally hosted by the Association for the Advancement of Artificial Intelligence at its annual conference. This program puts reusable equipment into schools and, at the Botball Teacher Workshops, trains teachers in robotics and the integration of robotics into their curriculum.

The debut of the AI in the News column elsewhere in this issue of AI Magazine created a good opportunity to introduce the professional community to the AI Topics web site, home of the AI in the news virtual page. Although AI Topics is designed for the lay public, it serves a much larger audience.

(IKS 2002).

"Neats and scruffies alike were mesmerized by the animal-like responses of the robots demonstrated there," says Bonasso. "At the end of "This won't be a slick, polished competition. Over the AAAI Mobile Robot Competition and Exhibition years, the event and AI Magazine have served as was born. The event has endured to a venue for this and several other intellectual become the oldest AIcentric robotics competition debates, including sensing versus modeling, in the world. As we near the end of our color-based versus shape-based object recognition, first decade, it seems worthwhile to reflect on and reactive control versus symbolic what the origins of the event were, how it has planning for robot navigation (Balch et al. evolved, and where it is headed. The contest immediately took on two important but apparently conflicting roles: First, it provided a target for research in AI and robotics; in Pete Bonasso's words, the event was cast "in the spirit of trying to develop as animate, responsive, and intelligent robot behavior as possible" (Dean and Bonasso 1993).

Botball is a national program in which teams of middle and high school students design, build, and program small autonomous mobile robots to compete in a highly charged interactive (but nondestructive) tournament. Botball students learn to program in c, construct feedback and control loops, create electromechanical systems, and integrate it all together while they work on a team. Botball takes place in regional tournaments across the country and culminates in a National Botball Tournament traditionally hosted by the Association for the Advancement of Artificial Intelligence at its annual conference. This program puts reusable equipment into schools and, at the Botball Teacher Workshops, trains teachers in robotics and the integration of robotics into their curriculum. Botball appeals to a wide variety of students and brings out the best in each, challenging them to solve realworld problems in a dynamic environment at their own level.

The AAAI Press - Distributed by The MIT Press Massachusetts Institute of Technology, 5 Cambridge Center, Cambridge, Massachusetts 02142 To order, call toll free: (800) 356-0343 or (617) 625-8569. SPRING 2002 5 first time that AAAI's National conference has been held in Canada--a In addition, the program chairs are experimenting with a new format for AAAI.