The Tower of Knowledge architecture integrates probability theory and logic for making decisions. The scheme models the causal dependencies between the functionalities of objects and their descriptions, and then employs the maximum expected utility principle, which combines probability theory and logic, to select the most appropriate label for the object. Since most existing scene interpretatio...

Marcet and Marimon (1994, revised 1998) developed a recursive saddle point method which can be used to solve dynamic contracting problems that include participation, enforcement and incentive constraints. Their method uses a recursive multiplier to capture implicit prior promises to the agent(s) that were made in order to satisfy earlier instances of these constraints. As a result, their method...

Abstract We analyze the impact of risk aversion and ambiguity on competing demands for annuities bequeathable savings using a lifecycle recursive utility model. Our main finding is that have similar effects: an increase in either two reduces annuity demand enhances bond holdings. obtain this unequivocal result flexible intertemporal framework Hayashi Miao (2011) by assuming agent’s preferences ...

A summary is given of the dynamicoptimization approach to speedup learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term "optimal" relative to the source of input instances and sketch an algorithm that can come within a logarithmic...

In this paper we develop a stochastic realization theory for multiscale autoregressive (MAR) processes that leads to computationally ecient realization algorithms. The utility of MAR processes has been limited by the fact that the previously known general purpose realization algorithm, based on canonical correlations, leads to model inconsistencies and has complexity quartic in problem size. O...

We study abstract macroeconomic systems in which expectations play an important role. Consistent with the recent literature on recursive learning and expectations, we replace the agents in the economy with econometricians. Unlike the recursive learning literature, however, the econometricians in the analysis here are Bayesian learners. We are interested in the extent to which expectational stab...

Résumé/Abstract: In this talk, we present three versions of maximum principle for a stochastic optimal control problem of Markov regime-switching forward-backward stochastic differential equations with jumps (FBSDEJs). A general sufficient maximum principle for optimal control for a system driven by a Markov regime-switching forward and backward jump-diffusion model is developed. After, an equi...

In this correspondence, we present a general recursive approach for image segmentation by extending Otsu’s method. The new approach has been implemented in the scope of document images, specifically real-life bank checks. This approach segments the brightest homogeneous object from a given image at each recursion, leaving only the darkest homogeneous object after the last recursion. The major s...

One of the most evident premises for successful E-Commerce transaction should lie in as much detailed recognition of personal customers’ differentiation as it becomes possible through the usage of multiple data resources available over the Internet. The methodical basis for the evaluation and subsequent utilization of all available data may be formed under the well known concepts of the utility...

We study a discrete-time finite-horizon two-player nonzero-sum stopping game where the filtration of Player 1 is richer than 2. A major difficulty which caused by information asymmetry that 2 may not know whether has already stopped or not. Furthermore, classical backward-induction approach applicable in current setup. This because when informed player decides to stop, he reveals uninformed pla...