This book is a collection of many of the seminal papers from the first decade of research in artificial intelligence in medicine (AIM). The editors state that the need for such a collection became evident when a two-day AIM tutorial was held at Stanford in 1980, following the annual national AIM research workshop. The 19 papers included in the book are each introduced by a short section written by the editors. Typically one page in length, these introductory sections are designed to place the paper into context in the field. In addition, the editors have included introductory and concluding chapters of their own.

A numeric representation of uncertain and incomplete sensor knowledge called certainty grids was used successfully in several recent mobile robot control programs developed at the Carnegie-Mellon University Mobile Robot Laboratory (MRL) Certainty grids have proven to be a powerful and efficient unifying solution for sensor fusion, motion planning, landmark identification, and many other central problems MRL had good early success with ad hoc formulas for updating grid cells with new information. A new Bayesian statistical foundation for the operations promises further improvement MRL proposes to build a software framework running on processors onboard the new Uranus mobile robot that will maintain a probabilistic, geometric map of the robot's surroundings as it moves, The certainty grid representation will allow this map to be incrementally updated in a uniform way based on information coming from various sources, including sonar, stereo vision, proximity, and contact sensors The approach can correctly model the fuzziness of each reading and, at the same time, combine multiple measurements to produce sharper map features; it can also deal correctly with uncertainties in the robot's motion The map will be used by planning programs to choose clear paths, The certainty grid representation can be extended in the time dimension and used to detect and track moving objects Even the simplest versions of the idea allow us to fairly straightforwardly program the robot for tasks that have hitherto been out of reach MRL looks forward to a program that can explore a region and return to its starting place, using map "snapshots" from its outbound journey to find its way back, even in the presence of disturbances Objects have been modeled by polygons and polyhedra or bounded by curved surfaces. Free space has been partitioned into Vornoi regions or, heuristically, free corridors. Traditionally, the models have been hard edged; positional uncertainty, if considered at all, was used in just a few special places in the algorithms, expressed as a Gaussian spread. Partly, this oversimplification of uncertainty information is the result of analytic difficulty in manipulating interacting uncertainties, especially if the distributions are not Gaussian.

The question of whether a computer can think like a person is once again a hot topic. Somewhat to my surprise, this philosophical question seems to have direct practical implications for AI, especially language understanding. The following analysis has been helpful to me and might be of some value to others. When we use words such as think, understand, and wish, we typically refer to the human experience of these activities. When I want to emphasize this point, I use the notation x/h for human.

Column n The Educational Advances in Artificial Intelligence column discusses and shares innovative educational approaches that teach or leverage AI and its many subfields at all levels of education (K-12, undergraduate, and graduate levels). By restructuring the course into a format that was roughly half lecture and half small-group problem solving, I was able to significantly increase student engagement, their understanding and retention of difficult concepts, and my own enjoyment in teaching the class. The ACTIVE Center's design was based on research on the power of collaborative learning to promote student success and retention, particularly for women, underrepresented minorities, and transfer students, who benefit greatly from building stronger connections with their peers through shared active learning experiences (Zhao, Carini, and Kuh 2006; Rypisi, Malcolm, and Kim 2009; Kahveci, Southerland, and Gilmer 2006). The ACTIVE Center, a 40-student classroom, includes movable furniture (20 trapezoidal tables and 40 lightweight rolling chairs) that is typically grouped into 10 hexagonal table clusters but that can also be arranged into lecture-style rows, a boardroom or seminar-style rectangular layout, or individual pair-activity tables. The room also has an Epson Brightlink "smart projector" at the front of the room, four flat-panel displays (which can be driven centrally by the instructor's laptop or individually through HDMI ports), and 10 rolling 4 x 6 foot whiteboards for use during group problem-solving activities, as well as smaller, portable tabletop whiteboards.

Everyday, we depend on many systems and machines. We use a car to travel, a lift go up and down, and a plane to fly. Electricity comes through turbines and in a hospital machine keeps us alive. Some failures are an just an inconvenience, while others could mean life or death. When stakes are high, we perform regular maintenance on our systems.

Everyday, we depend on many systems and machines. We use a car to travel, a lift go up and down, and a plane to fly. Electricity comes through turbines and in a hospital machine keeps us alive. Some failures are an just an inconvenience, while others could mean life or death. When stakes are high, we perform regular maintenance on our systems.

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