Mechanism design has found considerable application to the construction of agent-interaction protocols. In the standard setting, the type (e.g., utility function) of an agent is not known by other agents, nor is it known by the mechanism designer. When this uncertainty is quantified probabilistically, a mechanism induces a game of incomplete information among the agents. However, in many settin...

In this paper we present LazyBrush, a novel interactive tool for painting hand-made cartoon drawings and animations. Its key advantage is simplicity and flexibility. As opposed to previous custom tailored approaches [SBv05, QWH06] LazyBrush does not rely on style specific features such as homogenous regions or pattern continuity yet still offers comparable or even less manual effort for a broad...

John D. Kueck and Brendan J. Kirby John D. Kueck is a Staff Engineer within the Power Systems Research Program at Oak Ridge National Laboratory, where he has served for a decade in a career that has also included service with Sargent & Lundy Engineers, Combustion Engineering, and Carolina Power & Light Co. In his 30 years in the field, Mr. Kueck’s work has spanned the electrical design and oper...

Scoring rules for eliciting expert predictions of random variables are usually developed assuming that experts derive utility only from the quality of their predictions (e.g., score awarded by the rule, or payoff in a prediction market). We study a more realistic setting in which (a) the principal is a decision maker and will take a decision based on the expert’s prediction; and (b) the expert ...

In the standard mechanism design setting, the type (e.g., utility function) of an agent is not known by other agents, nor is it known by the mechanism designer. When this uncertainty is quantified probabilistically, a mechanism induces a game of incomplete information among the agents. However, in many settings, uncertainty over utility functions cannot easily be quantified. We consider the pro...

In this paper we present a procedure for representing the semantics of linear hybrid automata (LHAs) as constraint logic programs (CLP); flexible and accurate analysis and verification of LHAs can then be performed using generic CLP analysis and transformation tools. LHAs provide an expressive notation for specifying real-time systems. The main contributions are (i) a technique for capturing th...

There are several methods for Multi Criteria Decision Making (MCDM) such as multiple attribute utility theory (MAUT), the analytical hierarchy process (AHP), and Fuzzy AHP. However, these methods are compensatory optimization approaches for which bad score on some criteria can be compensated by excellent scores on other criteria. So, the Elimination and Choice Translating Reality III (ELECTRE I...

In this survey we discuss different state-of-the-art approaches of combining exact algorithms and metaheuristics to solve combinatorial optimization problems. Some of these hybrids mainly aim at providing optimal solutions in shorter time, while others primarily focus on getting better heuristic solutions. The two main categories in which we divide the approaches are collaborative versus integr...

This paper addresses the issue of the impact of aid supply on aid effectiveness. We proceed in two steps. First, we review research works that deal with the problem of governance in donor-recipient relationships and are susceptible of highlighting effects of aggregate aid availability. Second, we provide a conceptual framework that explicitly incorporates a trade-off between considerations of n...

We consider the problem of learning from revealed preferences in an online setting. In our framework, each period a consumer buys an optimal bundle of goods from a merchant according to her (linear) utility function and current prices, subject to a budget constraint. The merchant observes only the purchased goods, and seeks to adapt prices to optimize his profits. We give an efficient algorithm...