Representation recovers information

Early agreement within cognitive science on the topic of representation has now given way to a combination of positions. Some question the significance of representation in cognition. Others continue to argue in favor, but the case has not been demonstrated in any formal way. The present paper sets out a framework in which the value of representation-use can be mathematically measured, albeit in a broadly sensory context rather than a specifically cognitive one. Key to the approach is the use of Bayesian networks for modeling the distal dimension of sensory processes. More relevant to cognitive science is the theoretical result obtained, which is that a certain type of representational architecture is *necessary* for achievement of sensory efficiency. While exhibiting few of the characteristics of traditional, symbolic encoding, this architecture corresponds quite closely to the forms of embedded representation now being explored in some embedded/embodied approaches. It becomes meaningful to view that type of representation-use as a form of information recovery. A formal basis then exists for viewing representation not so much as the substrate of reasoning and thought, but rather as a general medium for efficient, interpretive processing

Dual-layer network representation exploiting information characterization

In this paper, a logical dual-layer representation approach is proposed to facilitate the analysis of directed and weighted complex networks. Unlike the single logical layer structure, which was widely used for the directed and weighted flow graph, the proposed approach replaces the single layer with a dual-layer structure, which introduces a provider layer and a requester layer. The new structure provides the characterization of the nodes by the information, which they provide to and they request from the network. Its features are explained and its implementation and visualization are also detailed. We also design two clustering methods with different strategies respectively, which provide the analysis from different points of view. The effectiveness of the proposed approach is demonstrated using a simplified example. By comparing the graph layout with the conventional directed graph, the new dual-layer representation reveals deeper insight into the complex networks and provides more opportunities for versatile clustering analysis.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

Medical Information Representation Framework for Mobile Healthcare

In mobile healthcare, medical information are often expressed in different formats due to the local policies and regulations and the heterogeneity of the applications, systems, and the adopted Information and communication technology. This chapter describes a framework which enables medical information, in particular clinical vital signs and professional annotations, be processed, exchanged, stored and managed modularly and flexibly in a mobile, distributed and heterogeneous environment despite the diversity of the formats used to represent the information. To deal with medical information represented in multiple formats the authors adopt techniques and constructs similar to the ones used on the Internet, in particular, the authors are inspired by the constructs used in multi-media e-mail and audio-visual data streaming standards. They additionally make a distinction of the syntax for data transfer and store from the syntax for expressing medical domain concepts. In this way, they separate the concerns of what to process, exchange and store from how the information can be encoded or transcoded for transfer over the internet. The authors use an object oriented information model to express the domain concepts and their relations while briefly illustrate how framework tools can be used to encode vital sign data for exchange and store in a distributed and heterogeneous environment

Lobbying, Information Transmission, and Unequal Representation

We study the effects of unequal representation in the interest-group system on the degree of information transmission between a lobbyist and a policymaker. Employing a dynamic cheap-talk model in which the lobbyist cares instrumentally about his reputation for truthtelling, we show that the larger is the inequality, the less information can credibly be transmitted to the policymaker. We also investigate the effects of inequality on welfare and discuss the welfare effects of institutions that increase transparency but which as well, as an unintended side-effect, lower the lobbyist's incentives for truthtelling.lobbying, interest groups, reputation, information transmission, representation, inequality, bias

Lobbying, Information Transmission, and Unequal Representation

We study the effects of unequal representation in the interest-group system on the degree of information transmission between a lobbyist and a policymaker. Employing a dynamic cheap-talk model in which the lobbyist cares instrumentally about his reputation for truthtelling, we show that the larger is the inequality, the less information can credibly be transmitted to the policymaker. We also investigate the effects of inequality on welfare and discuss the welfare effects of institutions that increase transparency but which as well, as an unintended side-effect, lower the lobbyist's incentives for truthtelling.lobbying, interest groups, reputation, information transmission, representation, inequality, bias