Modeling and Using Context


Book Description

This book constitutes the proceedings of the 9th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2015, held in Larnaca, Cyprus, in November 2015. The 33 full papers and 13 short papers presented were carefully reviewed and selected from 91 submissions. The main theme of CONTEXT 2015 was "Back to the roots", focusing on the importance of interdisciplinary cooperations and studies of the phenomenon. Context, context modeling and context comprehension are central topics in linguistics, philosophy, sociology, artificial intelligence, computer science, art, law, organizational sciences, cognitive science, psychology, etc. and are also essential for the effectiveness of modern, complex and distributed software systems. CONTEXT 2015 embedded also a Doctoral Symposium, and three workshops; Smart University 3.0; CATI: Context Awareness and Tactile Design for Mobile Interaction; and SHAPES 3.0: The Shape of Things.




Knowing and Checking


Book Description

Checking is a very common concept for describing a subject’s epistemic goals and actions. Surprisingly, there has been no philosophical attention paid to the notion of checking. This is the first book to develop a comprehensive epistemic theory of checking. The author argues that sensitivity is necessary for checking but not for knowing, thereby finding a new home for the much discussed modal sensitivity principle. He then uses the distinction between checking and knowing to explain central puzzles about knowledge, particularly those concerning knowledge closure, bootstrapping and the skeptical puzzle. Knowing and Checking: An Epistemological Investigation will be of interest to epistemologists and other philosophers looking for a general theory of checking and testing or for new solutions to central epistemological problems.







Welfare-maximizing Monetary Policy Under Parameter Uncertainty


Book Description

This paper examines welfare-maximizing monetary policy in an estimated micro-founded general equilibrium model of the U.S. economy where the policymaker faces uncertainty about model parameters. Uncertainty about parameters describing preferences and technology implies not only uncertainty about the dynamics of the economy. It also implies uncertainty about the model's utility-based welfare criterion and about the economy's natural rate measures of interest and output. We analyze the characteristics and performance of alternative monetary policy rules given the estimated uncertainty regarding parameter estimates. We find that the natural rates of interest and output are imprecisely estimated. We then show that, relative to the case of known parameters, optimal policy under parameter uncertainty responds less to natural-rate terms and more to other variables, such as price and wage inflation and measures of tightness or slack that do not depend on natural rates.




Combining Forecasts from Nested Models


Book Description

Motivated by the common finding that linear autoregressive models forecast better than models that incorporate additional information, this paper presents analytical, Monte Carlo, and empirical evidence on the effectiveness of combining forecasts from nested models. In our analytics, the unrestricted model is true, but as the sample size grows, the DGP converges to the restricted model. This approach captures the practical reality that the predictive content of variables of interest is often low. We derive MSE-minimizing weights for combining the restricted and unrestricted forecasts. In the Monte Carlo and empirical analysis, we compare the effectiveness of our combination approach against related alternatives, such as Bayesian estimation.




Taylor Rules


Book Description