50 research outputs found

    Magnifying Lens Abstraction for Stochastic Games with Discounted and Long-run Average Objectives

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    Turn-based stochastic games and its important subclass Markov decision processes (MDPs) provide models for systems with both probabilistic and nondeterministic behaviors. We consider turn-based stochastic games with two classical quantitative objectives: discounted-sum and long-run average objectives. The game models and the quantitative objectives are widely used in probabilistic verification, planning, optimal inventory control, network protocol and performance analysis. Games and MDPs that model realistic systems often have very large state spaces, and probabilistic abstraction techniques are necessary to handle the state-space explosion. The commonly used full-abstraction techniques do not yield space-savings for systems that have many states with similar value, but does not necessarily have similar transition structure. A semi-abstraction technique, namely Magnifying-lens abstractions (MLA), that clusters states based on value only, disregarding differences in their transition relation was proposed for qualitative objectives (reachability and safety objectives). In this paper we extend the MLA technique to solve stochastic games with discounted-sum and long-run average objectives. We present the MLA technique based abstraction-refinement algorithm for stochastic games and MDPs with discounted-sum objectives. For long-run average objectives, our solution works for all MDPs and a sub-class of stochastic games where every state has the same value

    The Road to General Intelligence

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    Humans have always dreamed of automating laborious physical and intellectual tasks, but the latter has proved more elusive than naively suspected. Seven decades of systematic study of Artificial Intelligence have witnessed cycles of hubris and despair. The successful realization of General Intelligence (evidenced by the kind of cross-domain flexibility enjoyed by humans) will spawn an industry worth billions and transform the range of viable automation tasks.The recent notable successes of Machine Learning has lead to conjecture that it might be the appropriate technology for delivering General Intelligence. In this book, we argue that the framework of machine learning is fundamentally at odds with any reasonable notion of intelligence and that essential insights from previous decades of AI research are being forgotten. We claim that a fundamental change in perspective is required, mirroring that which took place in the philosophy of science in the mid 20th century. We propose a framework for General Intelligence, together with a reference architecture that emphasizes the need for anytime bounded rationality and a situated denotational semantics. We given necessary emphasis to compositional reasoning, with the required compositionality being provided via principled symbolic-numeric inference mechanisms based on universal constructions from category theory. • Details the pragmatic requirements for real-world General Intelligence. • Describes how machine learning fails to meet these requirements. • Provides a philosophical basis for the proposed approach. • Provides mathematical detail for a reference architecture. • Describes a research program intended to address issues of concern in contemporary AI. The book includes an extensive bibliography, with ~400 entries covering the history of AI and many related areas of computer science and mathematics.The target audience is the entire gamut of Artificial Intelligence/Machine Learning researchers and industrial practitioners. There are a mixture of descriptive and rigorous sections, according to the nature of the topic. Undergraduate mathematics is in general sufficient. Familiarity with category theory is advantageous for a complete understanding of the more advanced sections, but these may be skipped by the reader who desires an overall picture of the essential concepts This is an open access book

    Magnifying lens abstraction for stochastic games with discounted and long-run average objectives

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    Turn-based stochastic games and its important subclass Markov decision processes (MDPs) provide models for systems with both probabilistic and nondeterministic behaviors. We consider turn-based stochastic games with two classical quantitative objectives: discounted-sum and long-run average objectives. The game models and the quantitative objectives are widely used in probabilistic verification, planning, optimal inventory control, network protocol and performance analysis. Games and MDPs that model realistic systems often have very large state spaces, and probabilistic abstraction techniques are necessary to handle the state-space explosion. The commonly used full-abstraction techniques do not yield space-savings for systems that have many states with similar value, but does not necessarily have similar transition structure. A semi-abstraction technique, namely Magnifying-lens abstractions (MLA), that clusters states based on value only, disregarding differences in their transition relation was proposed for qualitative objectives (reachability and safety objectives). In this paper we extend the MLA technique to solve stochastic games with discounted-sum and long-run average objectives. We present the MLA technique based abstraction-refinement algorithm for stochastic games and MDPs with discounted-sum objectives. For long-run average objectives, our solution works for all MDPs and a sub-class of stochastic games where every state has the same value

    SMT goes ABMS: Developing Strategic Management Theory using Agent-Based Modelling and Simulation.

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    For the emerging complexity theory of strategy (CTS), organizations are complex adaptive systems able to co-evolve with their dynamic environments through interaction and response, rather than purely analysis and planning. A promising approach within the CTS context, is to focus on a strategic logic of opportunity pursuit, one in which the distributed decision-makers behave audaciously despite unpredictable, unstable environments. Although there is only emergent support for it, intriguingly organizations can perform better when these decision-makers ‘throw caution to the wind’ even at their own possible expense. Since traditional research methods have had difficulty showing how this can work over time, this research adopts a complementary method, agent-based modelling and simulation (ABMS), to examine this phenomenon. The simulation model developed here, CTS-SIM, is based on quite simple constructs, but it introduces a rich and novel externally driven environment and represents individual decision-makers as having autonomous perceptions but constrainable decision-making freedom. Its primary contribution is the illumination of core dynamics and causal mechanisms in the opportunity-transitioning process. During model construction the apparently simple concept of opportunity-transitioning turns out to be complex, and the apparently complex integration of exogenous and endogenous environments with all three views of opportunity pursuit in the entrepreneurship literature, turns out to be relatively simple. Simulation outcomes using NetLogo contribute to CTS by confirming the positive effects on agent performance of opportunistic transitioning among opportunities in highly dynamic environments. The simulations also reveal tensions among some of the chosen variables and tipping points in emergent behaviours, point to areas where theoretical clarity is currently lacking, provoke some interesting questions and open up useful avenues for future research and data collection using other methods and models. Guidance through numerous stylized facts, flexible methods, careful documentation and description are all intended to inspire interest and facilitate critical discussion and ongoing scientific work

    3D-in-2D Displays for ATC.

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    This paper reports on the efforts and accomplishments of the 3D-in-2D Displays for ATC project at the end of Year 1. We describe the invention of 10 novel 3D/2D visualisations that were mostly implemented in the Augmented Reality ARToolkit. These prototype implementations of visualisation and interaction elements can be viewed on the accompanying video. We have identified six candidate design concepts which we will further research and develop. These designs correspond with the early feasibility studies stage of maturity as defined by the NASA Technology Readiness Level framework. We developed the Combination Display Framework from a review of the literature, and used it for analysing display designs in terms of display technique used and how they are combined. The insights we gained from this framework then guided our inventions and the human-centered innovation process we use to iteratively invent. Our designs are based on an understanding of user work practices. We also developed a simple ATC simulator that we used for rapid experimentation and evaluation of design ideas. We expect that if this project continues, the effort in Year 2 and 3 will be focus on maturing the concepts and employment in a operational laboratory settings

    Seventh Annual Workshop on Space Operations Applications and Research (SOAR 1993), volume 1

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    This document contains papers presented at the Space Operations, Applications and Research Symposium (SOAR) Symposium hosted by NASA/Johnson Space Center (JSC) on August 3-5, 1993, and held at JSC Gilruth Recreation Center. SOAR included NASA and USAF programmatic overview, plenary session, panel discussions, panel sessions, and exhibits. It invited technical papers in support of U.S. Army, U.S. Navy, Department of Energy, NASA, and USAF programs in the following areas: robotics and telepresence, automation and intelligent systems, human factors, life support, and space maintenance and servicing. SOAR was concerned with Government-sponsored research and development relevant to aerospace operations. More than 100 technical papers, 17 exhibits, a plenary session, several panel discussions, and several keynote speeches were included in SOAR '93

    Corporate Governance and the Shareholder: Asymmetry, Confidence, and Decision-Making

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    In the decade following the ten-plus percent stockmarket collapse of 2000, regulators enacted a myriad of regulations in response to increasing angst experienced by U.S. capital market retail investors. Systemic asymmetric disclosures have fractured investor confidence prompting many commentators to characterize the relationship between Wall Street and the investment community on main street as dire. Though copious works exist on the phenomenon of corporate behaviors, especially matters of shareholder welfare, weak boards, pervious governance mechanisms, and managerial excess, current literature has revealed a dearth in corporate governance praxis specific to the question and effects of asymmetric disseminations and its principal impact on the retail/noninstitutional accredited investor\u27s (NIAI) confidence and decision-making propensities. This phenomenological study is purposed to bridging the gap between the effects of governance disclosure and the confidence and decision-making inclinations of NIAIs. Conceptual frameworks of Akerlof\u27s information theory and Verstegen Ryan and Buchholtz\u27s trust/risk decision making model undergirded the study. A nonrandom purposive sampling method was used to select 21 NIAI informants. Analysis of interview data revealed epistemological patterns/themes confirming the deleterious effects of asymmetrical disseminations on participants\u27 investment decision-making and trust behaviors. Findings may help academicians, investors, policy makers, and practitioners better comprehend the phenomenon and possibly contribute to operating efficiencies in the capital markets. Proaction and greater assertiveness in the investor/activist community may provide an impetus for continued regulatory reforms, improved transparency, and a revitalization of public trust as positive social change outcomes

    Perspectives on Digital Humanism

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    This open access book aims to set an agenda for research and action in the field of Digital Humanism through short essays written by selected thinkers from a variety of disciplines, including computer science, philosophy, education, law, economics, history, anthropology, political science, and sociology. This initiative emerged from the Vienna Manifesto on Digital Humanism and the associated lecture series. Digital Humanism deals with the complex relationships between people and machines in digital times. It acknowledges the potential of information technology. At the same time, it points to societal threats such as privacy violations and ethical concerns around artificial intelligence, automation and loss of jobs, ongoing monopolization on the Web, and sovereignty. Digital Humanism aims to address these topics with a sense of urgency but with a constructive mindset. The book argues for a Digital Humanism that analyses and, most importantly, influences the complex interplay of technology and humankind toward a better society and life while fully respecting universal human rights. It is a call to shaping technologies in accordance with human values and needs

    Perspectives on Digital Humanism

    Get PDF
    This open access book aims to set an agenda for research and action in the field of Digital Humanism through short essays written by selected thinkers from a variety of disciplines, including computer science, philosophy, education, law, economics, history, anthropology, political science, and sociology. This initiative emerged from the Vienna Manifesto on Digital Humanism and the associated lecture series. Digital Humanism deals with the complex relationships between people and machines in digital times. It acknowledges the potential of information technology. At the same time, it points to societal threats such as privacy violations and ethical concerns around artificial intelligence, automation and loss of jobs, ongoing monopolization on the Web, and sovereignty. Digital Humanism aims to address these topics with a sense of urgency but with a constructive mindset. The book argues for a Digital Humanism that analyses and, most importantly, influences the complex interplay of technology and humankind toward a better society and life while fully respecting universal human rights. It is a call to shaping technologies in accordance with human values and needs
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