The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform
Fillia Makedon - One of the best experts on this subject based on the ideXlab platform.
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Approximate planning in POMDPs via MDP Heuristic
2014 International Joint Conference on Neural Networks (IJCNN), 2014Co-Authors: Xingjia Lu, Fillia MakedonAbstract:MDP Heuristic based POMDP algorithms have been considered as simple, fast, but imprecise solutions. This paper provides a novel MDP Heuristic Value iteration algorithm for POMDPs. Besides the help of MDP, our algorithm utilizes a weighted graph model for the belief point approximation and reassignment, to further improve the efficiency and decrease the space complexity. Experimental results indicate our algorithm is fast and has high solution quality for POMDP problems.
Patricia A Curtin - One of the best experts on this subject based on the ideXlab platform.
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examining the Heuristic Value of models of international public relations practice a case study of the arla foods crisis
Journal of Public Relations Research, 2007Co-Authors: Kenn T Gaither, Patricia A CurtinAbstract:When a Danish newspaper published cartoons of the prophet Muhammad in 2005, Danish food company Arla Foods saw its rapid growth in the Middle East halt and sales plummet in the region. Using Arla Foods as a case study, this article tests a critical cultural approach to international public relations through the cultural–economic model, based on the circuit of culture. The article summarizes limitations of the Western neoliberal model of international practice as a segue into the cultural–economic model. By using critical discourse analysis techniques to analyze communications materials from Arla and subsequent news coverage, the study extends international public relations theory and provides suggestions for international public relations best practices.
Claudio Bosio - One of the best experts on this subject based on the ideXlab platform.
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studying the social construction of cancer related fatigue experience the Heuristic Value of ethnoscience
Patient Education and Counseling, 2011Co-Authors: Guendalina Graffigna, Elena Vegni, Serena Barello, Karin Olson, Claudio BosioAbstract:Abstract Objectives Patients’ lived experience of illness and health is receiving increased attention in the medical field. Understanding patients’ perspective and experiences is an undoubted asset for efficient health interventions and improved clinical concordance. Patients’ experiences of care and cure, however, are influenced by the cultural setting in which these experiences take place. This implies that health interventions should be “ecological” and attuned to the specific sociocultural context of the patients. Methods Our research group is conducting a cross-cultural qualitative study aimed ad exploring how fatigue (a symptom very common in cancer) is perceived and manifested by patients in different countries (Canada, Thailand, England and Italy). In order to achieve this, the study was design according to the method of Ethnoscience, that appeared to us the best suited to explore the meanings that patients attribute to their state and the linguistic patterns they use to describe it. In this paper we will describe in details the process of Ethnoscience and will discuss the Heuristic Value of this research approach. Results Ethnoscience was an effective research strategy for exploring how beliefs and Values shape symptoms and the behavioural manifestations of cancer related fatigue. Conclusions This paper discusses the Heuristic Value of Ethnoscience and its applicability to the study of health relate topics, particularly those where issues of social construction are important. Practical implications Ethnoscience is a promising and innovative research approach, able to cast light on the way people experience and make sense of their illness.
Serena Barello - One of the best experts on this subject based on the ideXlab platform.
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studying the social construction of cancer related fatigue experience the Heuristic Value of ethnoscience
Patient Education and Counseling, 2011Co-Authors: Guendalina Graffigna, Elena Vegni, Serena Barello, Karin Olson, Claudio BosioAbstract:Abstract Objectives Patients’ lived experience of illness and health is receiving increased attention in the medical field. Understanding patients’ perspective and experiences is an undoubted asset for efficient health interventions and improved clinical concordance. Patients’ experiences of care and cure, however, are influenced by the cultural setting in which these experiences take place. This implies that health interventions should be “ecological” and attuned to the specific sociocultural context of the patients. Methods Our research group is conducting a cross-cultural qualitative study aimed ad exploring how fatigue (a symptom very common in cancer) is perceived and manifested by patients in different countries (Canada, Thailand, England and Italy). In order to achieve this, the study was design according to the method of Ethnoscience, that appeared to us the best suited to explore the meanings that patients attribute to their state and the linguistic patterns they use to describe it. In this paper we will describe in details the process of Ethnoscience and will discuss the Heuristic Value of this research approach. Results Ethnoscience was an effective research strategy for exploring how beliefs and Values shape symptoms and the behavioural manifestations of cancer related fatigue. Conclusions This paper discusses the Heuristic Value of Ethnoscience and its applicability to the study of health relate topics, particularly those where issues of social construction are important. Practical implications Ethnoscience is a promising and innovative research approach, able to cast light on the way people experience and make sense of their illness.
Xingjia Lu - One of the best experts on this subject based on the ideXlab platform.
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Approximate planning in POMDPs via MDP Heuristic
2014 International Joint Conference on Neural Networks (IJCNN), 2014Co-Authors: Xingjia Lu, Fillia MakedonAbstract:MDP Heuristic based POMDP algorithms have been considered as simple, fast, but imprecise solutions. This paper provides a novel MDP Heuristic Value iteration algorithm for POMDPs. Besides the help of MDP, our algorithm utilizes a weighted graph model for the belief point approximation and reassignment, to further improve the efficiency and decrease the space complexity. Experimental results indicate our algorithm is fast and has high solution quality for POMDP problems.
