Natural actor and belief critic: Reinforcement algorithm for learning parameters of dialogue systems modelled as POMDPs

This article presents a novel algorithm for learning parameters in statistical dialogue systems which are modeled as Partially Observable Markov Decision Processes (POMDPs). The three main components of a POMDP dialogue manager are a dialogue model representing dialogue state information; a policy that selects the system's responses based on the inferred state; and a reward function that specifies the desired behavior of the system. Ideally both the model parameters and the policy would be designed to maximize the cumulative reward. However, while there are many techniques available for learning the optimal policy, no good ways of learning the optimal model parameters that scale to real-world dialogue systems have been found yet. The presented algorithm, called the Natural Actor and Belief Critic (NABC), is a policy gradient method that offers a solution to this problem. Based on observed rewards, the algorithm estimates the natural gradient of the expected cumulative reward. The resulting gradient is then used to adapt both the prior distribution of the dialogue model parameters and the policy parameters. In addition, the article presents a variant of the NABC algorithm, called the Natural Belief Critic (NBC), which assumes that the policy is fixed and only the model parameters need to be estimated. The algorithms are evaluated on a spoken dialogue system in the tourist information domain. The experiments show that model parameters estimated to maximize the expected cumulative reward result in significantly improved performance compared to the baseline hand-crafted model parameters. The algorithms are also compared to optimization techniques using plain gradients and state-of-the-art random search algorithms. In all cases, the algorithms based on the natural gradient work significantly better. © 2011 ACM.

Parameters influencing the performance of an IGBT gate drive

This paper presents an improvement of an IGBT gate drive implementing Active Voltage Control (AVC), and investigates the impact of various parameters affecting its performance. The effects of the bandwidths of various elements and the gains of AVC are shown in simulation and experimentally. Also, the paper proposes connecting a small Active Snubber between the IGBT collector and its gate integrated within the AVC. The effect of this snubber on enhancing the stability of the gate drive is demonstrated. It will be shown that using a wide bandwidth operational amplifier and integrating the Active Snubber within the gate drive reduces the minimum gate resistor required to achieve stability of the controller. Consequently, the response time of the IGBT to control signals is significantly reduced, the switching losses then can be minimised and, hence, the performance of gate drive as whole is improved. This reflects positively on turn-off and turn-on transitions achieving voltage sharing between the IGBTs connected in series to construct a higher voltage switch, making series IGBTs a feasible practice. ©2008 IEEE.

Parameters identification by a single point free response measurement

When a thin rectangular plate is restrained on the two long edges and free on the remaining edges, the equivalent stiffness of the restraining joints can be identified by the order of the natural frequencies obtained using the free response of the plate at a single location. This work presents a method to identify the equivalent stiffness of the restraining joints, being represented as simply supporting the plate but elastically restraining it in rotation. An integral transform is used to map the autospectrum of the free response from the frequency domain to the stiffness domain in order to identify the equivalent torsional stiffness of the restrained edges of the plate and also the order of natural frequencies. The kernel of the integral transform is built interpolating data from a finite element model of the plate. The method introduced in this paper can also be applied to plates or shells with different shapes and boundary conditions. © 2011 Elsevier Ltd. All rights reserved.

The energy required to produce materials: constraints on energy-intensity improvements, parameters of demand.

In this paper, we review the energy requirements to make materials on a global scale by focusing on the five construction materials that dominate energy used in material production: steel, cement, paper, plastics and aluminium. We then estimate the possibility of reducing absolute material production energy by half, while doubling production from the present to 2050. The goal therefore is a 75 per cent reduction in energy intensity. Four technology-based strategies are investigated, regardless of cost: (i) widespread application of best available technology (BAT), (ii) BAT to cutting-edge technologies, (iii) aggressive recycling and finally, and (iv) significant improvements in recycling technologies. Taken together, these aggressive strategies could produce impressive gains, of the order of a 50-56 per cent reduction in energy intensity, but this is still short of our goal of a 75 per cent reduction. Ultimately, we face fundamental thermodynamic as well as practical constraints on our ability to improve the energy intensity of material production. A strategy to reduce demand by providing material services with less material (called 'material efficiency') is outlined as an approach to solving this dilemma.