38,361 research outputs found

    Constructive Decision Theory

    Get PDF
    Contemporary approaches to decision making describe a decision problem by sets of states and outcomes, and a rich set of acts: functions from states to outcomes over which the decision maker (DM) has preferences. Real problems do not come so equipped. It is often unclear what the state and outcome spaces would be. We present an alternative foundation for decision making, in which the primitive objects of choice are syntactic programs. We show that if the DM's preference relation on objects of choice satisfies appropriate axioms, then we can find states, outcomes, and an embedding of the programs into Savage acts such that preferences can be represented by EU in the Savage framework. A modeler can test for SEU behavior without having access to the subjective states and outcomes. We illustrate the power of our approach by showing that it can represent DMs who are subject to framing effects.Decision theory, subjective expected utility, behavioral anomalies

    100 Ideas for Upgrading the Association Agreements and DCFTAs with Georgia, Moldova and Ukraine. CEPS Policy Insights No 2020-02 / February 2020

    Get PDF
    There are now many ideas in circulation to enhance the Association Agreements (AA), which include the Deep and Comprehensive Free Trade Areas (DCFTA), stimulated in part by the ‘Structured Consultation’ on the future of the Eastern Partnership (EaP) initiated by the Commission in 2019. All three AA states made detailed submissions; the present note seeks to incorporate these and other ideas into the makings of a possible initiative to upgrade the agreements and give them renewed and politically significant momentu

    Towards Intelligent Databases

    Get PDF
    This article is a presentation of the objectives and techniques of deductive databases. The deductive approach to databases aims at extending with intensional definitions other database paradigms that describe applications extensionaUy. We first show how constructive specifications can be expressed with deduction rules, and how normative conditions can be defined using integrity constraints. We outline the principles of bottom-up and top-down query answering procedures and present the techniques used for integrity checking. We then argue that it is often desirable to manage with a database system not only database applications, but also specifications of system components. We present such meta-level specifications and discuss their advantages over conventional approaches

    Convergence in Models with Bounded Expected Relative Hazard Rates

    Full text link
    We provide a general framework to study stochastic sequences related to individual learning in economics, learning automata in computer sciences, social learning in marketing, and other applications. More precisely, we study the asymptotic properties of a class of stochastic sequences that take values in [0,1][0,1] and satisfy a property called "bounded expected relative hazard rates." Sequences that satisfy this property and feature "small step-size" or "shrinking step-size" converge to 1 with high probability or almost surely, respectively. These convergence results yield conditions for the learning models in B\"orgers, Morales, and Sarin (2004), Erev and Roth (1998), and Schlag (1998) to choose expected payoff maximizing actions with probability one in the long run.Comment: After revision. Accepted for publication by Journal of Economic Theor

    Relational Representations in Reinforcement Learning: Review and Open Problems

    Get PDF
    This paper is about representation in RL.We discuss some of the concepts in representation and generalization in reinforcement learning and argue for higher-order representations, instead of the commonly used propositional representations. The paper contains a small review of current reinforcement learning systems using higher-order representations, followed by a brief discussion. The paper ends with research directions and open problems.\u
    corecore