Models of Cognition: Neurological possibility does not indicate neurological plausibility

Many activities in Cognitive Science involve complex computer models and simulations of both theoretical and real entities. Artificial Intelligence and the study of artificial neural nets in particular, are seen as major contributors in the quest for understanding the human mind. Computational models serve as objects of experimentation, and results from these virtual experiments are tacitly included in the framework of empirical science. Cognitive functions, like learning to speak, or discovering syntactical structures in language, have been modeled and these models are the basis for many claims about human cognitive capacities. Artificial neural nets (ANNs) have had some successes in the field of Artificial Intelligence, but the results from experiments with simple ANNs may have little value in explaining cognitive functions. The problem seems to be in relating cognitive concepts that belong in the `top-down' approach to models grounded in the `bottom-up' connectionist methodology. Merging the two fundamentally different paradigms within a single model can obfuscate what is really modeled. When the tools (simple artificial neural networks) to solve the problems (explaining aspects of higher cognitive functions) are mismatched, models with little value in terms of explaining functions of the human mind are produced. The ability to learn functions from data-points makes ANNs very attractive analytical tools. These tools can be developed into valuable models, if the data is adequate and a meaningful interpretation of the data is possible. The problem is, that with appropriate data and labels that fit the desired level of description, almost any function can be modeled. It is my argument that small networks offer a universal framework for modeling any conceivable cognitive theory, so that neurological possibility can be demonstrated easily with relatively simple models. However, a model demonstrating the possibility of implementation of a cognitive function using a distributed methodology, does not necessarily add support to any claims or assumptions that the cognitive function in question, is neurologically plausible

Integration of multi-scale biosimulation models via light-weight semantics

Currently, biosimulation researchers use a variety of computational environments and languages to model biological processes. Ideally, researchers should be able to semi- automatically merge models to more effectively build larger, multi-scale models. How- ever, current modeling methods do not capture the underlying semantics of these models sufficiently to support this type of model construction. In this paper, we both propose a general approach to solve this problem, and we provide a specific example that demon- strates the benefits of our methodology. In particular, we describe three biosimulation models: (1) a cardio-vascular fluid dynamics model, (2) a model of heart rate regulation via baroreceptor control, and (3) a sub-cellular-level model of the arteriolar smooth mus- cle. Within a light-weight ontological framework, we leverage reference ontologies to match concepts across models. The light-weight ontology then helps us combine our three models into a merged model that can answer questions beyond the scope of any single model

Proceedings of the ECSCW'95 Workshop on the Role of Version Control in CSCW Applications

The workshop entitled "The Role of Version Control in Computer Supported Cooperative Work Applications" was held on September 10, 1995 in Stockholm, Sweden in conjunction with the ECSCW'95 conference. Version control, the ability to manage relationships between successive instances of artifacts, organize those instances into meaningful structures, and support navigation and other operations on those structures, is an important problem in CSCW applications. It has long been recognized as a critical issue for inherently cooperative tasks such as software engineering, technical documentation, and authoring. The primary challenge for versioning in these areas is to support opportunistic, open-ended design processes requiring the preservation of historical perspectives in the design process, the reuse of previous designs, and the exploitation of alternative designs. The primary goal of this workshop was to bring together a diverse group of individuals interested in examining the role of versioning in Computer Supported Cooperative Work. Participation was encouraged from members of the research community currently investigating the versioning process in CSCW as well as application designers and developers who are familiar with the real-world requirements for versioning in CSCW. Both groups were represented at the workshop resulting in an exchange of ideas and information that helped to familiarize developers with the most recent research results in the area, and to provide researchers with an updated view of the needs and challenges faced by application developers. In preparing for this workshop, the organizers were able to build upon the results of their previous one entitled "The Workshop on Versioning in Hypertext" held in conjunction with the ECHT'94 conference. The following section of this report contains a summary in which the workshop organizers report the major results of the workshop. The summary is followed by a section that contains the position papers that were accepted to the workshop. The position papers provide more detailed information describing recent research efforts of the workshop participants as well as current challenges that are being encountered in the development of CSCW applications. A list of workshop participants is provided at the end of the report. The organizers would like to thank all of the participants for their contributions which were, of course, vital to the success of the workshop. We would also like to thank the ECSCW'95 conference organizers for providing a forum in which this workshop was possible

Multiple Retrieval Models and Regression Models for Prior Art Search

This paper presents the system called PATATRAS (PATent and Article Tracking, Retrieval and AnalysiS) realized for the IP track of CLEF 2009. Our approach presents three main characteristics: 1. The usage of multiple retrieval models (KL, Okapi) and term index definitions (lemma, phrase, concept) for the three languages considered in the present track (English, French, German) producing ten different sets of ranked results. 2. The merging of the different results based on multiple regression models using an additional validation set created from the patent collection. 3. The exploitation of patent metadata and of the citation structures for creating restricted initial working sets of patents and for producing a final re-ranking regression model. As we exploit specific metadata of the patent documents and the citation relations only at the creation of initial working sets and during the final post ranking step, our architecture remains generic and easy to extend