640 research outputs found

    Does Russia Need a Securities Law?

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    The question in the title of this article is not necessarily rhetorical. Perhaps a more appropriate inquiry is, does Russia need its current securi- ties law?\u27 The response to the titular question is, as I will argue, clearly yes. The answer to the second question is to a large extent negative. Given the prevailing economic conditions in Russia, the course of enterprise pri- vatization, and the principal institutions shaping Russian capital markets, there is good reason to think that rather than assisting the growth and en- trenchment of a market in securities, much of the current Russian securities legislation will be superfluous and possibly hinder such growth

    Diamond v. Chakrabarty: Gauging Congress’s Response to Dynamic Statutory Interpretation by the Supreme Court

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    A comparative study on the path length performance of maze-searching and robot motion planning algorithms

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    Diamond v. Chakrabarty: Gauging Congress’ Response to Dynamic Statutory Interpretation by the Supreme Court

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    In this article, I consider the 1980 Supreme Court decision, Diamond v. Chakrabarty, and Congress’ response to it in light of several contemporary views on statutory interpretation. I conclude that in science and technology-related cases in which delay could significantly hamper the advancement of the field, the Supreme Court should interpret federal statutes dynamically in response to a changing social context, but should also attempt to conform its interpretations to legislative preferences in order to avoid a legislative override

    Final Report for the DARPA/NSF Interdisciplinary Study on Human–Robot Interaction

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    As part of a Defense Advanced Research Projects Agency/National Science Foundation study on human–robot interaction (HRI), over sixty representatives from academia, government, and industry participated in an interdisciplinary workshop, which allowed roboticists to interact with psychologists, sociologists, cognitive scientists, communication experts and human–computer interaction specialists to discuss common interests in the field of HRI, and to establish a dialogue across the disciplines for future collaborations. We include initial work that was done in preparation for the workshop, links to keynote and other presentations, and a summary of the findings, outcomes, and recommendations that were generated by the participants. Findings of the study include— the need for more extensive interdisciplinary interaction, identification of basic taxonomies and research issues, social informatics, establishment of a small number of common application domains, and field experience for members of the HRI community. An overall conclusion of the workshop was expressed as the following— HRI is a cross-disciplinary area, which poses barriers to meaningful research, synthesis, and technology transfer. The vocabularies, experiences, methodologies, and metrics of the communities are sufficiently different that cross-disciplinary research is unlikely to happen without sustained funding and an infrastructure to establish a new HRI community

    Decentralized motion planning for multiple mobile robots: The cocktail party model

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    Abstract. This paper presents an approach for decentralized real-time motion planning for multiple mobile robots operating in a common 2-dimensional environment with unknown stationary obstacles. In our model, a robot can see (sense) the surrounding objects. It knows its current and its target’s position, is able to distinguish a robot from an obstacle, and can assess the instantaneous motion of another robot. Other than this, a robot has no knowledge about the scene or of the paths and objectives of other robots. There is no mutual communication among the robots; no constraints are imposed on the paths or shapes of robots and obstacles. Each robot plans its path toward its target dynamically, based on its current position and the sensory feedback; only the translation component is considered for the planning purposes. With this model, it is clear that no provable motion planning strategy can be designed (a simple example with a dead-lock is discussed); this naturally points to heuristic algorithms. The suggested strategy is based on maze-searching techniques. Computer simulation results are provided that demonstrate good performance and a remarkable robustness of the algorithm (meaning by this a virtual impossibility to create a dead-lock in a “random ” scene). Keywords: mobile robots, autonomous agents, decentralized intelligence, robot motion plannin
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