Rational Value of Information Estimation for Measurement Selection

Computing value of information (VOI) is a crucial task in various aspects of decision-making under uncertainty, such as in meta-reasoning for search; in selecting measurements to make, prior to choosing a course of action; and in managing the exploration vs. exploitation tradeoff. Since such applications typically require numerous VOI computations during a single run, it is essential that VOI be computed efficiently. We examine the issue of anytime estimation of VOI, as frequently it suffices to get a crude estimate of the VOI, thus saving considerable computational resources. As a case study, we examine VOI estimation in the measurement selection problem. Empirical evaluation of the proposed scheme in this domain shows that computational resources can indeed be significantly reduced, at little cost in expected rewards achieved in the overall decision problem.Comment: 7 pages, 2 figures, presented at URPDM2010; plots fixe

Rational Deployment of CSP Heuristics

Heuristics are crucial tools in decreasing search effort in varied fields of AI. In order to be effective, a heuristic must be efficient to compute, as well as provide useful information to the search algorithm. However, some well-known heuristics which do well in reducing backtracking are so heavy that the gain of deploying them in a search algorithm might be outweighed by their overhead. We propose a rational metareasoning approach to decide when to deploy heuristics, using CSP backtracking search as a case study. In particular, a value of information approach is taken to adaptive deployment of solution-count estimation heuristics for value ordering. Empirical results show that indeed the proposed mechanism successfully balances the tradeoff between decreasing backtracking and heuristic computational overhead, resulting in a significant overall search time reduction.Comment: 7 pages, 2 figures, to appear in IJCAI-2011, http://www.ijcai.org

An Estimated New Keynesian Model for Israel

We formulate and estimate a small New Keynesian model for the Israeli economy. Our goal is to construct a small but still realistic model that can be used to support the inflation targeting process. The model contains three structural equations: An open economy Phillips curve for CPI inflation (excluding the housing component), an aggregate demand curve for the output gap and an interest parity condition for the nominal exchange rate. The model is closed with an interest rate reaction function (Taylor-type rule) and an ad hoc equation for the housing component of the CPI, which is dominated by exchange rate changes. In the specification of the model we had to pay special attention to the crucial role of the exchange rate in the transmission of monetary policy in Israel, which has a direct effect on almost 60 percent of the CPI. The model is estimated by the GMM method, using quarterly data for the period 1992:I to 2005:IV. In the estimation of the structural equations we tried to remain as close as possible to the theoretical formulation by restricting the dynamics to one lag at most. We use the model to characterize an "optimal" simple interest rate rule. We find that the monetary authority should respond to an hybrid backward-forward looking rate of inflation and does not benefit from direct reaction to exchange rate measures.