Sequential decision making in general state space models

Many problems in control and signal processing can be formulated as sequential decision problems for general state space models. However, except for some simple models one cannot obtain analytical solutions and has to resort to approximation. In this thesis, we have investigated problems where Sequential Monte Carlo (SMC) methods can be combined with a gradient based search to provide solutions to online optimisation problems. We summarise the main contributions of the thesis as follows. Chapter 4 focuses on solving the sensor scheduling problem when cast as a controlled Hidden Markov Model. We consider the case in which the state, observation and action spaces are continuous. This general case is important as it is the natural framework for many applications. In sensor scheduling, our aim is to minimise the variance of the estimation error of the hidden state with respect to the action sequence. We present a novel SMC method that uses a stochastic gradient algorithm to find optimal actions. This is in contrast to existing works in the literature that only solve approximations to the original problem. In Chapter 5 we presented how an SMC can be used to solve a risk sensitive control problem. We adopt the use of the Feynman-Kac representation of a controlled Markov chain flow and exploit the properties of the logarithmic Lyapunov exponent, which lead to a policy gradient solution for the parameterised problem. The resulting SMC algorithm follows a similar structure with the Recursive Maximum Likelihood(RML) algorithm for online parameter estimation. In Chapters 6, 7 and 8, dynamic Graphical models were combined with with state space models for the purpose of online decentralised inference. We have concentrated more on the distributed parameter estimation problem using two Maximum Likelihood techniques, namely Recursive Maximum Likelihood (RML) and Expectation Maximization (EM). The resulting algorithms can be interpreted as an extension of the Belief Propagation (BP) algorithm to compute likelihood gradients. In order to design an SMC algorithm, in Chapter 8 uses a nonparametric approximations for Belief Propagation. The algorithms were successfully applied to solve the sensor localisation problem for sensor networks of small and medium size.

Poner el cuerpo. Mujeres y política estatal en Mari (Siglo XVIII a.c.)

Women and men are subjects defined both by their physical-natural reality and their socio-cultural environment. In this way they are reified, and many such examples can be found throughout history. We are interested in the situation of women in Ancient Mesopotamia, particularly the daughters of Zimrî-Lîm, king of the city of Mari, the archaeological site of Tell Hariri, modern Syria, during the 18th century BC. Zimrî- Lîm made marriages a policy of the state. He himself married foreign women and married their joint daughters to other important kings as well. This marital policy was another, more extended, way of dominion where women were a nexus between Mari and other states. In this paper, we will analyze the roles which were assigned and developed by royal women from a political level via a comprehensive approach. These women are presented generally as political objects, though, in extreme cases also they were taking forward actions as subjects and by it they were visualized as “the other,” the foreigner and, in some cases, the enemy.

Ausência de política pública de cotas raciais para ingresso em instituições públicas de ensino superior no Brasil

Descreve o atual panorama normativo para as cotas raciais no Brasil com base em estudo realizado com utilização de a análise documental e bibliográfica. Os resultados indicaram que a ausência de uma norma federal implicou baixa adesão ao sistema de cotas, o que é ratificado pelo insignificante número de Instituições Públicas de Ensino Superior (Ipes) que adotaram norma de cota racial - apenas 17,79%. Verificou-se, ainda, que essa ausência cria lacunas na adoção de diretrizes nacionais para a interpretação e a compreensão das ações afirmativas. Tais lacunas refletem diretamente no ciclo da política pública, comprometendo a avaliação e o acompanhamento da efetividade e do sucesso da política, o que é extremamente perigoso para a segurança jurídica na área de direitos humanos e para a garantia da equidade de fato nos espaços político, econômico e social.

Fiscal Policy and Economic Stability: Does PIGS stand for Procyclicality In Government Spending?

The Financial Crisis has hit particularly hard countries like Ireland or Spain. Procyclical fiscal policy has contributed to a boom-bust cycle that undermined fiscal positions and deepened current account deficits during the boom. We set up an RBC model of a small open economy, following Mendoza (1991), and introduce the effect of fiscal policy decisions that change over the cycle. We calibrate the model on data for Ireland, and simulate the effect of different spending policies in response to supply shocks. Procyclical fiscal policy distorts intertemporal allocation decisions. Temporary spending boosts in booms spur investment, and hence the need for external finance, and so generates very volatile cycles in investment and the current account. This economic instability is also harmful for the steady state level of output. Our model is able to replicate the relation between the degree of cyclicality of fiscal policy, and the volatility of consumption, investment and the current account observed in OECD countries.

On the Informational Role of Term Structure in the U.S. Monetary Policy Rule

This paper uses a structural approach based on the indirect inference principle to estimate a standard version of the new Keynesian monetary (NKM) model augmented with term structure using both revised and real-time data. The estimation results show that the term spread and policy inertia are both important determinants of the U.S. estimated monetary policy rule whereas the persistence of shocks plays a small but significant role when revised and real-time data of output and inflation are both considered. More importantly, the relative importance of term spread and persistent shocks in the policy rule and the shock transmission mechanism drastically change when it is taken into account that real-time data are not well behaved.