Logo Turtle Graphics for the Lisp Machine

This paper is a manual for an implementation of Logo graphics primitives in Lisp on the MIT Lisp Machine. The graphics system provides: Simple line drawing and erasing using "turtle geometry" Flexible relative and absolute coordinate systems, scaling Floating point coordinates Drawing points, circles, boxes, text Automatically filling closed curves with patterns Saving and restoring pictures rapidly as arrays of points Drawing on color displays, creating new colors Three dimensional perspective drawing, two-color stereo displayMIT Artificial Intelligence Laborator

End-User Software Engineering Position Paper

End-user software engineering position paper

Security and Modularity in Message Passing

This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Office of Naval Research of the Department of Defense under contract N00014-75-C-0522.This paper addresses theoretical issues involved for the implementation of security and modularity in concurrent systems. It explicates the theory behind a mechanism for safely delegating messages to shared handlers in order to increase the modularity of concurrent systems. Our mechanism has the property that the actions caused by delegated messages are atomic. That is the handling of a message delegated by a client actor appears to be indivisible to other users of the actor. Our mechanism for delegating communications is a generalization suitable for use in concurrent systems of the sub-class mechanism of SIMULA. Our mechanism has the benefit that it easily lends itself to the implementation of efficient flexible access control mechanisms in distributed systems. It is a generalization of the protection mechanisms provided by capability-based system, access control lists, and the access control mechanisms provided by PDP-10 SIMULA.MIT Artificial Intelligence Laboratory Department of Defense Office of Naval Researc

Breaking down brick walls: Design, construction, and prototype fabrication knowledge in architecture

Architectural designs are not just collections of 3D objects. Architects have both high-level aesthetic design intent, and intent for the functionality of the building; these must eventually translate into real-world construction materials and processes. Physical prototypes are still essential for the architect and their clients to get a feel for whether designs "work". An exciting recent development in architecture is the use of industrial robots to automatically construct 3D prototype architectural models. But programming the robots requires tedious procedures of low-level commands, far removed from the designer's intent. Adeon is a system that integrates high-level architectural design knowledge, including aesthetic and stylistic intent, with knowledge about materials and construction processes, and robot programming code for constructing prototype 3D physical models. It centers around collecting and associating "common sense" knowledge, expressed in English and converted to a knowledge representation about the various levels. It provides a graphic editor that allows architects to draw high-level aesthetic designs, perhaps referencing known styles or historical examples, and retrieving relevant construction, materials, and cost information. It automatically produces a robot program for constructing the prototype. We present examples detailing the design of various styles of brick walls. Adeon is an interesting example of how to provide an interface for creative work that spans both high-level and low-level concerns

Script-Based Story Matching for Cyberbullying Prevention

While the Internet and social media help keep today’s youth better connected to their friends, family, and community, the same media are also the form of expression for an array of harmful social behaviors, such as cyberbullying and cyber-harassment. In this paper we present work in progress to develop intelligent interfaces to social media that use commonsense knowledge bases and automated narrative analyses of text communications between users to trigger selective interventions and prevent negative outcomes. While other approaches seek merely to classify the overall topic of the text, we try to match stories to finer-grained “scripts” that represent stereotypical events and actions. For example, many bullying stories can be matched to a “revenge” script that describes trying to harm someone who has harmed you. These tools have been implemented in an initial prototype system and tested on a database of real stories of cyberbullying collected on MTV’s “A Thin Line” Web site

Common Sense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying

Cyberbullying (harassment on social networks) is widely recognized as a serious social problem, especially for adolescents. It is as much a threat to the viability of online social networks for youth today as spam once was to email in the early days of the Internet. Current work to tackle this problem has involved social and psychological studies on its prevalence as well as its negative effects on adolescents. While true solutions rest on teaching youth to have healthy personal relationships, few have considered innovative design of social network software as a tool for mitigating this problem. Mitigating cyberbullying involves two key components: robust techniques for effective detection and reflective user interfaces that encourage users to reflect upon their behavior and their choices. Spam filters have been successful by applying statistical approaches like Bayesian networks and hidden Markov models. They can, like Google’s GMail, aggregate human spam judgments because spam is sent nearly identically to many people. Bullying is more personalized, varied, and contextual. In this work, we present an approach for bullying detection based on state-of-the-art natural language processing and a common sense knowledge base, which permits recognition over a broad spectrum of topics in everyday life. We analyze a more narrow range of particular subject matter associated with bullying (e.g. appearance, intelligence, racial and ethnic slurs, social acceptance, and rejection), and construct BullySpace, a common sense knowledge base that encodes particular knowledge about bullying situations. We then perform joint reasoning with common sense knowledge about a wide range of everyday life topics. We analyze messages using our novel AnalogySpace common sense reasoning technique. We also take into account social network analysis and other factors. We evaluate the model on real-world instances that have been reported by users on Formspring, a social networking website that is popular with teenagers. On the intervention side, we explore a set of reflective user-interaction paradigms with the goal of promoting empathy among social network participants. We propose an “air traffic control”-like dashboard, which alerts moderators to large-scale outbreaks that appear to be escalating or spreading and helps them prioritize the current deluge of user complaints. For potential victims, we provide educational material that informs them about how to cope with the situation, and connects them with emotional support from others. A user evaluation shows that in-context, targeted, and dynamic help during cyberbullying situations fosters end-user reflection that promotes better coping strategies

NLP (Natural Language Processing) for NLP (Natural Language Programming)

This paper discusses Natural Language Processing (NLP)