Optimizing Dialog Strategies for Conversational Agents Interacting in AmI Environments

Proceedings of: 3rd International Symposium on Ambient Intelligence (ISAmI 2012). Salamanca (Spain), 28-30 March 2012In this paper, we describe a conversational agent which provides academic information. The dialog model of this agent has been developed by means of a statistical methodology that automatically explores the dialog space and allows learning new enhanced dialog strategies from a dialog corpus. A dialog simulation technique has been applied to acquire data required to train the dialog model and then explore the new dialog strategies. A set of measures has also been defined to evaluate the dialog strategy. The results of the evaluation show how the dialogmodel deviates from the initially predefined strategy, allowing the conversational agent to tackle new situations and generate new coherent answers for the situations already present in the initial corpus. The proposed technique can be used not only to develop new dialog managers but also to explore new enhanced dialog strategies focused on user adaptation required to interact in AmI environments.Research funded by projects CICYT TIN2011-28620-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad

Agent Simulation to Develop Interactive and User-Centered Conversational Agents

Proceedings of: International Symposium on Distributed Computing and Artificial Intelligence (DCAI 2011). Salamanca, 06-08 April 2011.In this paper, we present a technique for developing user simulators which are able to interact and evaluate conversational agents. Our technique is based on a statistical model that is automatically learned from a dialog corpus. This model is used by the user simulator to provide the following answer taking into account the complete history of the interaction. The main objective of our proposal is not only to evaluate the conversational agent, but also to improve this agent by employing the simulated dialogs to learn a better dialog model. We have applied this technique to design and evaluate a conversational agent which provides academic information in a multi-agent system. The results of the evaluation show that the conversational agent reduces the time needed to fulfill to complete the the dialogs, thereby allowing the conversational agent to tackle new situations and generate new coherent answers for the situations already present in an initial model.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02- 02/TEC, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad

Regularized Neural User Model for Goal-Oriented Spoken Dialogue Systems

User simulation is widely used to generate artificial dialogues in order to train statistical spoken dialogue systems and perform evaluations. This paper presents a neural network approach for user modeling that exploits an encoder-decoder bidirectional architecture with a regularization layer for each dialogue act. In order to minimize the impact of data sparsity, the dialogue act space is compressed according to the user goal. Experiments on the Dialogue State Tracking Challenge 2 (DSTC2) dataset provide significant results at dialogue act and slot level predictions, outperforming previous neural user modeling approaches in terms of F1 score.Spanish Minister of Science under grants TIN2014-54288-C4-4-R and TIN2017-85854-C4-3-R and by the EU H2020 EMPATHIC project grant number 769872

Meteorology applied to urban air pollution problems: concepts from COST 715

International audienceThis selective review of the COST 715 considers simple descriptive concepts in urban meteorology with particular attention to air pollution assessment. It is shown that these are helpful for understanding the complex structure of the urban boundary layer, but that simple concepts only apply under a limited number of occasions. However such concepts are necessary for insight into how both simple and complex air pollution models perform. Wider considerations are needed when considering routine air quality assessments involving an air quality model's formulation and pedigree. It is argued that there is a reluctance from model developers to move away from familiar concepts of the atmospheric boundary layer even if they are not appropriate to urban areas. An example is given from COST 715 as to how routine urban meteorological measurements of wind speed may be used and adapted for air quality assessments. Reference to the full COST 715 study is made which provides further details

Meteorology applied to urban air pollution problems: concepts from COST 715

International audienceThe outcome of COST 715 is reviewed from the viewpoint of a potential user who is required to consider urban meteorology within an air pollution assessment. It is shown that descriptive concepts are helpful for understanding the complex structure of the urban boundary layer, but that they only apply under a limited number of conditions. However such concepts are necessary to gain insight into both simple and complex air pollution models. It is argued that wider considerations are needed when considering routine air quality assessments involving an air quality model's formulation and pedigree. Moreover there appears to be a reluctance from model developers to move away from familiar concepts of the atmospheric boundary layer even if they are not appropriate to urban areas. An example is given from COST 715 as to how routine urban meteorological measurements of wind speed may be used and adapted for air quality assessments. Reference to the full COST 715 study is made which provides further details

The Coronal Structure of AB Doradus

We perform a numerical simulation of the corona of the young, rapidly rotating K0 dwarf AB Doradus using a global MHD model. The model is driven by a surface map of the radial magnetic field constructed using Zeeman-Doppler Imaging. We find that the global structure of the stellar corona is dominated by strong azimuthal tangling of the magnetic field due to the rapid rotation. The MHD solution enables us to calculate realistic Alfv\'en surfaces and we can therefore estimate the stellar mass loss rate and angular momentum loss rate without making undue theoretical simplifications. We consider three cases, parametrized by the base density of the corona, that span the range of possible solutions for the system. We find that overall, the mass and angular-momentum loss rates are higher than in the solar case; the mass loss rates are 10 to 500 times higher, and the angular momentum loss rate can be up to $3\times{10}^4$ higher than present day solar values. Our simulations show that this model can be use to constrain the wide parameter space of stellar systems. It also shows that an MHD approach can provide more information about the physical system over the commonly used potential field extrapolation.Comment: 13 pages, 7 figure

Development and validation of tools for the implementation of european air quality policy in Germany (Project VALIUM)

International audienceIn the framework of the German Atmospheric Research Program AFO-2000 a system of consistent coupled numerical models has been developed. The purpose of the model system is to serve as a tool for the execution of European urban air quality regulations. A consortium with the acronym VALIUM was formed, which consisted of German research institutes, environmental consultancies and an environmental agency. A substantial part of the VALIUM program was devoted to the generation of a set of high quality data for the validation of the numerical model system. The validation data are based on a combination of field studies, tracer experiments and corresponding wind tunnel experiments. The field experiments were carried out inside and around a street canyon in a city district of Hanover/Germany. After a brief introduction to the VALIUM project a summary of the main results will be given

Soft Computing Models for the Development of Commercial Conversational Agents

Proceedings of: 6th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2011). Salamanca, April 6-8, 2011In this paper we present a proposal for the development of conversational agents that, on the one hand, takes into account the benefits of using standards like VoiceXML, whilst on the other, includes a module with a soft computing model that avoids the effort of manually defining the dialog strategy. This module is trained using a labeled dialog corpus, and selects the next system response considering a classification process based on neural networks that takes into account the dialog history. Thus, system developers only need to define a set of VoiceXML files, each including a system prompt and the associated grammar to recognize the users responses to the prompt. We have applied this technique to develop a conversational agent in VoiceXML that provides railway information in Spanish.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02- 02/TEC, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad