The ICCBR-workshops "Cognitive Approaches in Memory-Based Reasoning" and "Human Centered Case-Based Reasoning" are joining forces: there is considerable overlap in the topics we want to address, and we have decided on a single workshop under the banner "Human-Centered and Cognitive Approaches to Case-Based Reasoning". We will publish more information on our plans shortly.
The submission system is now closed for new submissions of full papers. PC members can access submitted papers at: www.easychair.org/conferences/?conf=iccbr2011.
We would like to encourage the late submission of position papers. Such papers should have a length of up to 2 pages in the Springer LNCS format. Details on the submission procedure will be published shortly.
The problem-solving environment has changed dramatically in recent years. The internet offers immediate access to vast knowledge repositories on the web and the growth of social network sites is adding a new layer of almost real time data. Domain ontologies and linked data are starting to provide a level of structure to these knowledge repositories. Interacting with the data should not just be about retrieval; rather we have to learn how to reason with this data either in an automated way or through human/machine interaction. CBR must evolve new strategies if it is to provide effective reasoning systems in this new problem-solving environment.
The traditional decomposition adopted in CBR describes a set of experience as fixed problem and solution components. This static problem-solving model may no longer apply. Humans want adaptive, interactive systems and not stand alone systems. Problem-solving tends to be typified by flexible, evolving tasks being solved with rapidly changing, distributed knowledge sources. CBR must develop new strategies to address these changes and integrate them into the problem-solving process.
We would like this forum to encourage CBR researchers to take a new look at our cognitive roots and at what we have been doing. Rather than seeking incremental performance gains in our algorithms are there bigger problems that have longer term implications in making our problem-solving experiences better? How can we break these bigger problems up into sub-problems that we can work on, in shorter time frames?
The workshop's broad goals include: (1) identifying different cognitive approaches to reasoning and how they relate to CBR, (2) examining how new cognitive strategies can be exploited within the CBR cycle, and (3) advancing the state of the art in relation to CBR systems. To achieve this we propose to incorporate the following activities in the workshop: