Data Mining in Functional Genomics and Proteomics: Current Trends and Future Directions.

Configuration Workshop

The 4th International Cognitive Robotics Workshop (CogRob-2004)

First European Workshop on Chance Discovery (EWCD-04)

Workshop on Knowledge Management and Organizational Memories

Second Workshop on Agents Applied in Health Care

Agents in dynamic and real-time environments

Hybrid Metaheuristics (HM 2004)

International Workshop on Semantic Intelligent Middleware for the Web and the Grid (WS 10 AND WS 24 HAVE BEEN MERGED)

Multi-Agent Markov Decision Processes: Theories and Models

4th Workshop on Computational Models of Natural Argument (CMNA 4)

2nd International Workshop on Adaptive Multimedia Retrieval (AMR 2004)

Workshop on Modelling and Solving Problems with Constraints

Spatial and Temporal Reasoning

Ontology Learning and Population: Towards Evaluation of Text-based Methods in the Semantic Web and Knowledge Discovery Life Cycle

1st Workshop on ROC Analysis in AI

Constraint Satisfaction Techniques for Planning and Scheduling Problems

4th Workshop on Binding Environmental Sciences and Artificial Intellenge (BESAI'2004)

Workshop on application of Semantic Web technologies to Web Communities

MONET Workshop on Model-Based Systems

W01

Data Mining in Functional Genomics and Proteomics: Current Trends and Future Directions.

Contact:  Dr. A.Fazel Famili

Abstract
Data Mining in Functional Genomics and Proteomics involves a close collaboration between researchers from a number of diverse areas, such as biology, medicine, genomics and proteomics to computer science, mathematics and statistics. This collaboration has evolved because of the: (i) advances in data production and acquisition facilities, such as the introduction of mircroarrays and high throughput genomics and proteomics, (ii) enormous amounts of data generated every day that cannot be analyzed using ordinary data mining tools and techniques, and (iii) strong interest from many groups who want to benefit from this wealth of data. Many efforts to deal with these issues are being undertaken by researchers working in this field.  The aim of this workshop is to bring together researchers working on different topics related to data mining in functional genomics and proteomics. In particular we are interested to focus on current trends and emphasize on what should be the future directions for generic and applied research in this field. The main topics to be addressed during the workshop are integration methodologies for functional genomics and proteomics and also issues related to structuring and disseminating all useful knowledge that increasingly becomes available in this field.

W02

Configuration Workshop

Contact:  Claire Bagley

Abstract
Representing and solving configuration problems have always been subjects of interest for applying and developing AI techniques because powerful knowledge-representation models are necessary to capture the great variety and complexity of configurable product models, and efficient reasoning methods are required to provide intelligent interactive behavior in configurator software, such as solution search, satisfaction of user preferences, optimization, etc.  Today, the number, the diversity and the complexity of configurable products available on the market is growing, expanding from conventional equipment configuration to service configuration. Configuration is more than ever a challenging area for applying novel AI techniques since more and more sophisticated reasoning tasks are delegated to the configurator software; the software must thus integrate product-assembly knowledge along with customer classification, adaptive sales strategies, and customer assistance. This integration becomes particularly critical for e-business applications where customers directly configure products through the Web with no human assistance and without a deep knowledge of the products they are buying. The workshop gives AI researchers from different areas, real-application developers, and industrial configurator vendors the opportunity to exchange needs, ideas, work, methods, experiments, user-cases, and benchmarks related to the various problems met by configuration applications: knowledge representation, reasoning, diagnosis, solution repair, interactivity, ontology, cooperative processes, etc. Additionally, the workshop hopes to attract case studies of applying configurators in organizations, including results from operation management researchers and others who may take a "black-box" perspective.

W03

The 4th International Cognitive Robotics Workshop (CogRob-2004)

Contact:  Patrick Doherty

Abstract
Research in robotics has traditionally emphasized low-level sensing and control tasks including sensory processing, path planning, and manipulator design and control. In contrast, research in cognitive robotics is concerned with endowing robots and software agents with higher level cognitive functions that enable them to reason, act and perceive in changing, incompletely known, and unpredictable environments.  Such robots must, for example, be able to reason about goals, actions, when to perceive and what to look for, the cognitive states of other agents, time, collaborative task execution, etc. In short, cognitive robotics is concerned with integrating reasoning, perception and action with a uniform theoretical and implementation framework.  Combining results from the traditional robotics discipline with those from AI and cognitive science has and will continue to be central to research in cognitive robotics.
This workshop aims to bring together researchers involved in all aspects of the theory and implementation of cognitive  robotics, to discuss current work and future directions.  While all aspects of cognitive robotics are of interest to the workshop, we especially welcome discussions and demonstrations of implemented systems.

W04

First European Workshop on Chance Discovery (EWCD-04)

Contact:  Ruediger Oehlmann

Abstract
In a number of different areas, researchers in Artificial Intelligence became recently interested in events or situations that affect human decision making in that they are viewed as opportunities or risks. A chance is such a rare event or a situation, which provides opportunities or risks for human decision making or problem solving. Noticing such an event is described as discovery of a chance. Therefore Chance Discovery can be characterized in terms of  

· becoming aware of a chance and

· explaining its significance.

In this sense, the discovery of a chance is emphasized in contrast to discovery by chance. The essential aspect of a chance is that it can be the seed of new and significant changes in the near future. Generally this means that being aware of a rare or novel important event without ignoring it as noise is essential for future success.

Therefore the workshop will discuss theories, methodologies and applications related to

· Identifying rare or novel events

· Becoming aware of significant events

· Predicting future trends

· Integrating knowledge of significant events with existing knowledge

· Explaining and evaluating events where decision makers still have to become aware of its significance (hidden event).

W05

Workshop on Symbolic Networks

Contact:  José M. Sempere

Abstract
Symbolic   networks  are   mathematic   constructions   in   which  the  information is   represented mainly by strings or multisets of abstract  symbols and it is   processed  in  a  cooperative,  distributed, and/or  parallel  manner. The   interest   of  this  kind  of  architectures in Artificial  Intelligence  has   been  always  maintained  in  different  research areas such as temporal logics, belief networks or  generalized  semantic  networks,  with  special  emphasis  in  applications  such as natural  language processing  and pattern recognition. Here, we propose  a  workshop  focused  in this  kind of formal architectures inspired by different  theories  ( mainly  biology,    computability  and   control  processing).  The  scope  of  this workshop  is summarized in different  topics such as, but not restricted to: "Bioinspired" architectures (tissue P systems and other variants of P system networks, DNA based networks, etc), Networks of evolutionary processors, Neural networks (specially Siegelmann's artificial recurrent neural networks and McCulloch-Pitts neural networks) and other architectures and related topologies.

W06

Workshop on Knowledge Management and Organizational Memories

Contact:  Rose Dieng and Nada Matta

Abstract
Knowledge Management (KM) aims at capturing explicit and tacit knowledge of an organization in order to facilitate the access, sharing, and reuse of that knowledge as well as creation of new knowledge and  organizational learning. KM must be guided by a strategic vision to fulfill its primary organizational objectives: improving knowledge sharing and cooperative work inside the organization; disseminating best practices; improving relationships with the external world; preserving past knowledge of the organization for reuse; improving the  quality of projects and innovations; anticipating the evolution of the external environment; and preparing for unexpected events and managing urgency and crisis situations. One approach for KM consists of building a corporate memory or organizational memory (OM). Several techniques can be considered, according to the type of organization, its needs and its culture: knowledge-based approaches, document-based approaches, workflow-based approches, CBR-based approaches, CSCW and cooperative approaches, ontology-based approaches, corporate Semantic Webs, Web-based approaches, agent-based approaches, distributed OMs,etc.
Several scenarios of KM can be tackled through OMs: project memory, skills management, communities of practice, strategic or technological watch,etc. The workshop aims at gathering researchers from multiple  disciplines,industrial participants and students in order to discuss models, methodologies, techniques and application scenarios useful for building, using, managing, evaluating and evolving corporate memories.

W07

Second Workshop on Agents Applied in Health Care

Contact:  John Nealon

Abstract
The workshop continues the series began at ECAI-2002, in Lyon, where the first specialised workshop on Agents Applied in Health Care was held. Extended versions of a selection of the papers presented at the first workshop are available in AI-Communications (Volume 16, Number 3 / 2003). This area of research and development has grown considerably over the last seven years or so, as it has become apparent that many problems in health care can be solved or partially solved through the use of agent-based systems. This has arisen since, often, health care at local, regional, national and international levels is characterized by shared and distributed decision making and management of care, requiring the communication of complex and diverse forms of information between a variety of clinical and other settings, as well as the coordination between groups of health care professionals with very different skills and roles. The workshop is intended as a forum for the exchange of ideas, where views and experience of both methodological and technological problems associated with the development of agent-based applications can be aired, and as a source of dissemination and promotion of agent-based developments in all types of medical, health and social care domains.

W08

Agents in dynamic and real-time environments

Contact:  Ubbo Visser

Abstract
Recent developments in multiagent systems (MAS) have been promising by achieving autonomous, collaborative behavior between agents in various environments. However, most of the agents, both software agents and physical agents, still have problems if the environment is dynamic and the agents have to act in real time. Examples are obstacle avoidance with moving obstacles or world models which are composed from egocentric views of numerous agents. Another aspect is the need for quick responses. In an environment where a number of agents build a team and both single agent decisions and team collaborative decisions have to be made methods have to be fast and precise. This workshop addresses various problems that occur with respect to these issues.

W09

Hybrid Metaheuristics (HM 2004)

Contact:  Christian Blum and Michael Sampels

Abstract
Metaheuristics, such as simulated annealing, genetic and evolutionary algorithms, tabu search, ant colony optimization, scatter search and iterated local search, have received considerable interest in the fields of applied artificial intelligence and combinatorial optimization.  Plenty of hard problems in a huge variety of areas, including bioinformatics, logistics, engineering, business, etc., have been tackled successfully with metaheuristic approaches. For many years the main focus of research was on the application of single metaheuristics to given problems. In recent years, it has become evident that the concentration on a sole metaheuristic is rather restrictive. A skilled combination of concepts of different metaheuristics, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility when dealing with real-world and large-scale problems. A quite new field of research is also the hybridization of metaheuristics with other techniques, such as constraint programming. This workshop is devoted to the design and implementation of hybrid metaheuristics. The scope of relevant subjects includes but is not limited to: novel combinations of components from different metaheuristics, hybridization of metaheuristics and more classical AI and OR techniques, relay hybridization, low- and high-level hybridization, portfolio techniques, co-operative search, taxonomy, classification of hybrid metaheuristics, population-based techniques, co-evolution techniques, advanced local-search and gradient techniques, automated parameter tuning, empirical and statistical comparison, parallelization, software libraries.

W10+W24

International Workshop on Semantic Intelligent Middleware for the Web and the Grid  (WS 10 AND WS 24 HAVE BEEN MERGED)

Contact:  Manolis Koubarakis

Abstract
The scientific paradigms of the Semantic Web, Software Agents, Peer-to-Peer Networks and Grid Computing are currently receiving a lot of attention, and are producing solutions to important problems ranging from e-science to e-business. The United States, the European Commission, Japan and other countries have been investing heavily in these technologies recently. The proposed workshop aims to foster international collaboration among the above areas of research and technological development with the aim to realize the vision of the Semantic Grid. The workshop is collocated with the premier European AI conference to emphasize the role of Artificial Intelligence techniques (e.g., knowledge representation, planning, learning etc.) in making progress in the above four areas and the ultimate realization of the Semantic Grid.
The workshop is in association with the Global Grid Forum Semantic Grid Research Group (http://www.semanticgrid.org).

W11

Multi-Agent Markov Decision Processes: Theories and Models

Contact:  Abdel-illah Mouaddib

Abstract
This workshop will present an opportunity for researchers working on the problems of multi-agent and interactive decision processes to share recent developments and techniques in this topic. In fact, the principal goal of the workshop is to bridge the existing gaps between the different techniques and to advance towards the construction of realistic systems that integrate different capabilities that now exist in isolation : multi-agent systems, protocols of communication, cooperation/negotiation, Markov decision processes, Markov Games, .....
This workshop will be organized around a set of challenge problems, posed by representatives of both the decision theory community and the multi-agent community.

W12

4th Workshop on Computational Models of Natural Argument (CMNA 4)

Contact:  Floriana Grasso

Abstract
AI has witnessed a growth in uses of research in the philosophical theory of argumentation, in informal logic, and in dialectics throughout many of its subdisciplines. Recent successes include agent system negotiation protocols that demonstrate higher levels of sophistication and robustness; argumentation-based models of evidential relations and legal processes that are more expressive; models of language generation that use rhetorical structures to produce effective arguments; groupwork tools that use argument to structure interaction and debate; computer-based learning tools that exploit monological and dialogical argument structures in designing pedagogic environments; decision support systems that build upon argumentation theoretic models of deliberation to better integrate with human reasoning; and models of knowledge engineering structured around core concepts of argument to simplify knowledge elicitation and representation problems. Similarly, argumentation theory has benefitted from applied AI work on new tools for teaching and research in argumentation and critical thinking, and from AI problems and issues that have offered a proving ground and evaluation framework for theories of argumentation.  Since 2001, the CMNA series, now at its fourth edition, with its focus on models of "natural" argumentation, has been acting to support this community of researchers, working in the field overlapping Argumentation Theory and AI.

W13

2nd International Workshop on Adaptive Multimedia Retrieval (AMR 2004)

Contact:  Andreas Nürnberger

Abstract
So far, several approaches have been developed that tackle specific problems of the retrieval process, e.g. feature extraction methods for multimedia data, query languages, problem specific similarity measures and interactive user interfaces. However, in most cases the user still needs several steps in order to find the searched objects. The main reasons for this are on the one hand, the users’ difficulty in specifying their interests in the form of a well defined, on the other hand, the problem of extracting relevant features from the multimedia objects. Furthermore, user specific interests and the search context are usually neglected when objects are retrieved. To improve today’s retrieval tools and thus the overall satisfaction of a user, it is necessary to develop intelligent methods that are able to support the user in the search process.
The goals of the workshop are to intensify the exchange of ideas between different research communities, to provide an overview of current activities in this area and to point out connections between the diverse involved research communities and research in AI.

W14

Workshop on Modelling and Solving Problems with Constraints

Contact:  Brahim Hnich

Abstract
Many companies have scheduling, assignment, supply chain and other problems that could be solved with a constraint programming (CP) toolkit. Although the solution of these problems is of vital commercial importance, CP toolkits are not widely used because there is limited expertise available to model and solve problems as constraint programs.
Modelling has been an active research area for a number of years. However,one major problem is that effective modelling often requires trying alternate models and selecting a model and a solver that efficiently solve the problem. Both of these tasks are still an art due to the combinatorial number of choices. In addition, problems are often over-constrained and the user has preferences for which constraints to relax. Finally, whilst much work in algorithm development is for satisfaction problems, many problems met in practice are naturally optimization problems.
When given a real-world application, one has to take two major, and closely related, decisions: how to model the considered problem, and how to solve the proposed model. Problem modelling cannot be separated from problem solving. Many modelling decisions have a direct impact on the kind of techniques that can be used by the solving method.

W15

Spatial and Temporal Reasoning

Contact:  Hans W. Guesgen

Abstract
Recent contributions to IJCAI, AAAI, and ECAI conferences and workshops show that reasoning about time and space has emerged as a major field of interest in AI.  This workshop is intended as a forum for discussion, exchange of points of view, assessment of results and methods, and as a source of dissemination and promotion of the newest advances in the area of spatial and temporal reasoning with a focus on the integration of various aspects and/or approaches.  Recent years have witnessed remarkable advances in some of the longstanding problems of the field (for instance, new results about tractability for spatial calculi, explicit construction of models, characterization of important subclasses of relations), as well as in the development of new areas (the appearance of new integrated spatio-temporal calculi is one example, as well as the development of multi-dimensional spatial calculi).  Likewise, proposals have been made to remedy some of the weak points of the symbolic approach, by introducing fuzzy versions of classical calculi, or importing non-monotonic techniques for dealing with incomplete information.  At the same time, leaders in AI have articulated the need for solving real problems and making the work on representation and reasoning relevant to the real world.

W16

Planning and Scheduling: Bridging Theory to Practice

Contact:  Daniel Borrajo

Abstract
The goal of the workshop consists on trying to understand and bridge the gap that currently exists between the very efficient planning&scheduling (P&S) technology and its application to real world domains. One way of bridging this gap would be through the integration of P&S techniques, but then more powerful techniques, tools, and languages would be required. Another way would be through the definition of more powerful user interfaces that would allow a non-planning expert to define new domains, reuse previous ones, run planners and schedulers using a mixed initiative approach, or evaluate plans. A third way of having more applications would be to enhance the P&S capabilities on handling uncertainty, and the relation of planning and execution. A fourth way would be by defining Web services based on P&S techniques that could receive problems and domains, and return a solution to them through well defined Web interfaces. In this workshop, we would like to discuss these applied research directions together with any other alternative direction that would allow to bridge the gap.
We invite researchers to submit papers on any of these previous topics, such as: knowledge engineering and planning&scheduling (P&S), integration of P&S, mixed initiative approaches to P&S, P&S and execution, P&S Web services, or success stories of applications.

W17

Workshop on Applications of Software Agents in Engineering

Contact:  Javier Carbo

Abstract
Software agents are computer programs that are able to perform autonomous and independent actions. Due to substantial progress during the last years in the area of (distributed) artificial intelligence (AI), software agents have been successfully applied in problems of the domain of engineering sciences such as sensor management, planning operations, image processing, etc.
The objective of this workshop is to offer a collection of high-quality contributions that reflect and advance the state-of-the art in the application of software agents to solve real-world problems. The workshop is focused on how (industrial rather than academic) problems of engineering may be faced by AI techniques involving the use of autonomous agents.

W18

Ontology Learning and Population: Towards Evaluation of Text-based Methods in the Semantic Web and Knowledge Discovery Life Cycle

Contact:  Paul Buitelaar, Siegfried Handschuh and Bernardo Magnini

Abstract
Ontologies are formal, explicit specifications of shared conceptualizations, representing concepts and their relations that are relevant for a given domain of discourse. Currently, ontologies are mostly developed as well as used by a manual process, which is very ineffective and may cause major barriers to their large-scale use in such areas as Knowledge Discovery and Semantic Web. As human language is a primary mode of knowledge transfer, automation of these tasks can be implemented by a combined use of linguistic analysis and machine learning approaches for text mining. The workshop will therefore be concerned with reports on the development of such methods, but specifically also with the quantitative evaluation of these methods. This is a central issue as it is currently very hard to compare methods and approaches, due to the lack of a shared understanding of the task at hand. The core theme of the workshop therefore will be to develop such a shared understanding through the definition of a clear task (and corresponding sub-tasks), identify resources needed for the task/sub-tasks and to discuss how best to develop an open source evaluation platform.

W19

1st Workshop on ROC Analysis in AI

Contact:  José Hernández-Orallo

Abstract
Receiver Operating Characteristic Analysis (ROC Analysis) is related in a direct and natural way to cost/benefit analysis of diagnostic decision making. Widely used in medicine for many decades, it has been introduced relatively recently in some areas of artificial intelligence: machine learning, multiagent systems, intelligent decision support and expert systems. In this context, ROC analysis provides tools to select possibly optimal models and to discard suboptimal ones independently from (and prior to specifying) the cost context or the class distribution. Furthermore, the Area Under the ROC Curve (AUC) has been shown to be a better evaluation measure than accuracy in contexts with variable misclassification costs and/or imbalanced datasets. AUC is also the standard measure when using classifiers to rank examples, and, hence, is used in applications where ranking is crucial, such as campaign design, model combination, collaboration strategies, and co-learning.
Nevertheless, there are many open questions and some limitations that hamper a broader use and applicability of ROC analysis. Its connections with other evaluation measures is not yet clarified completely, its incorporation in decision support and expert systems technology just envisaged, its use for improving the decisions of (communities of) intelligent agents unexplored, and its use in data mining still below its full potential.

W20

Constraint Satisfaction Techniques for Planning and Scheduling Problems

Contact:  Miguel A. Salido

Abstract
Nowadays, many important practical problems require efficient allocation of resources to competing goal activities over time in the presence of complex state-dependent constraints. Some example of this type of problems are synchronizing the on-board activities of a space mission, coordinating the movement of personnel and supplies to support disaster relief efforts, and managing the flow of materials through an automated manufacturing facility. Such problems are typically classified as scheduling problems, where resources must be allocated so as to optimize overall performance objectives (e.g., maximizing scientific return of space missions, initiating relief efforts as soon as possible, maximizing product throughput). At the same time, since the executability of a given goal activity in such problems also depends on conditions of the predicted world state other than resource availability (e.g., spacecraft vibration level, the locations of transport or material handling vehicles), solution feasibility can only be guaranteed by dynamically generating and synchronizing the auxiliary activities necessary to bring about and preserve enabling state conditions. Thus, solutions to these problems must integrate resource allocation and plan synthesis capabilities. In short, we need manage complex problems where planning, scheduling and constraint satisfaction must be interrelated. The aim of this workshop is to join researchers of the field of Artificial Intelligence working on planning, scheduling, constraint satisfaction problems (CSPs), temporal knowledge representation, reasoning problems and many other common areas that exist between them. In fact, most of the works are based on combined approaches of temporal reasoning and planning, scheduling and planning, planning and learning, knowledge representation or constraint satisfaction.

W21

Artificial Intelligence in Computer Supported Collaborative Learning

Contact:  Elena Gaudioso

Abstract
AI in Computer supported collaborative learning (CSCL) is an emerging paradigm for research in educational technology that integrates information, communication, and mediating technologies to support groups of learners that work together to achieve common goals.
Supporting group learning requires an understanding of the collaborative learning process, which is shaped not only by the individual's ability, learning style, and motivation, but also the group members' individual behaviors, and the dynamics of their interaction. Although CSCL research area can benefit from the lessons learned in similar AI application areas (such as intelligent tutoring systems), the collaborative environment increases the complexity of the environment by generating a significant amount of rich additional information concerning the joint work between students and their relationships.
The new information to be represented in the models for collaborative environments includes information about the users, the group and the collaboration and relationships between users.  The goal of this workshop is to show how Artificial Intelligence techniques, such as machine learning, planning or multi-agent approaches, can facilitate the representation, learning and inference of knowledge about the collaborative process, allowing the modeling and understanding of the outcomes.

W22

Workshop on local computation for logics and uncertainty

Contact:  Nic Wilson

Abstract
Local computation on acyclic hypertrees (and related graphical structures) has proved to be a very general method of computing deductions in knowledge representation formalisms. It has been shown to be applicable, in particular, to probabilities, possibility theory and other uncertainty calculi, constraints including finite constraints, soft constraints, linear constraints and inequalities, and a wide range of logics, including propositional and first-order classical logics and modal logics.
The purpose of the workshop is to bring together for the first time a group of researchers interested in the theory, the methods and applications of local computation (or computations based on hypertrees). Of interest are local computation in logic (satisfiability, consequence finding or other), uncertainty (probabilistic, possibilistic, belief functions or other), constraint solving  (crisp or soft constraints), data bases, optimization and decision problems, or its application to any other field. We welcome, for example, contributions regarding architectures and software for local computation, and specialist algorithms that only apply to some formalisms.

W23

4th Workshop on Binding Environmental Sciences and Artificial Intelligence (BESAI'2004)

Contact:  Mihaela Oprea and Miquel Sànchez-Marrè

Abstract
This workshop aspires to be an open forum for exposing and discussing the advances of international funded projects in the area, and bring together an interdisciplinary community of researchers with common interests in Artificial Intelligence and Environmental Sciences. This time will be the fourth edition of BESAI workshop under  the ECAI conference (1st BESAI'98 at Brighton, 2nd BESAI'2000 at Berlin, and 3rd BESAI'2002 at Lyon), and we hope its high level of participation and success will continue in València. Environmental Studies and Artificial Intelligence are both of strategic interest. Both areas can provide society with solutions for many real applications, in order to use and protect the environment. Human activities imply intervention into nature, but properly managed, these interventions can be not only ecologically sound but also favourable to the continued growth of civilisation. The encounter between these fields is a new challenge for many researchers of both communities. Also, governmental agencies may be interested in BESAI'2004 workshop.
The BESAI 2004 workshop recognizes the critical importance of environment and resource issues and their relationships with artificial intelligence (AI) research. The workshop's central focus is the linkage between patterns of AI activity and the environment with a major emphasis on translating the scientific basis for environmental concern into techniques and strategies that address both the needs of human societies and the requirements of natural systems. The workshop intends to create a discussion platform for AI and environmental science researchers

W25

Coordination in Emergent Agent Societies

Contact:  George A. Vouros

Abstract
Agent societies are coherently structured groups of agents whose behaviour is constrained by social laws. Agents in such groups plan and act so as to increase their own utility in conjunction to society's fitness advantage. An emergent agent society constitutes an open system whose structure, laws and individuals change depending on individual agents' capabilities, knowledge, resources, constraints agents face, and the dynamic nature of the environment in which agents' plan and act. A lot of work is devoted to formalizing and devising architectures for agents' cooperative behaviour, for coordinating the behaviour of individual agents within groups, as well as to designing agent societies using social laws. However, providing agents with abilities to automatically devise societies so as to form coherent emergent groups that coordinate their behaviour via social laws, is highly challenging. The objective of this workshop is to report on methods and techniques towards the formation of emergent agent societies that constrain their own behaviour, with the aim to coordinate their activities in highly distributed, dynamic and unpredictable environments.

W26

Workshop on application of Semantic Web technologies to Web Communities

Contact:  Rubén Lara

Abstract
Various communities have taken advantage of the current Web functionalities to strengthen the communication and information exchange not only within the community, but also with external communities or individual users. Miscellaneous web portals have appeared with the purpose of providing an open and effective communication forum for their members.
Nevertheless, current Web technology presents serious limitations to make information efficiently accessible for users. Moreover, users face the task of reading the documents retrieved in order to extract the information desired. These limitations naturally appear in existing Web communities based on this technology, making information searching, accessing, extracting, interpreting and processing a difficult and time-consuming task.
In this context, Semantic Web technologies can considerably improve the information sharing process, overcoming the problems found in current Web communities to search, access, extract, interpret and process information. In this sense, Web communities based on Semantic Web technologies represent a natural evolution of existing Web communities.
The workshop will provide a forum for workers in the fields of knowledge engineering, knowledge management, knowledge representation, language technology, ontological engineering, data, text and web mining and Semantic Web, to present their latest results and to discuss the potential joint application of these fields to Web communities, both analysing what has been achieved so far and what are the next steps to accomplish. The aim is to provide a snapshot of the state of the art and guidelines for further steps.

W27

Agent-Mediated Knowledge Management (AMKM-04)

Contact:  Andreas Abecker

Abstract
Knowledge Management is not only an important field of application for AI and Semantic Web technologies (ontologies, CBR, learning text classification, …), it also provides new challenges, like context-aware knowledge delivery. Scaling-up prototypes to real-world solutions requires an application-driven integration of basic technologies, e.g., ontologies for knowledge sharing and reuse plus collaboration support like CSCW systems, and personalized information services. Typical characteristics of such an integration are: (1) manifold logically and physically dispersed actors and knowledge sources; (2) different degrees of formalization of knowledge; (3) different kinds of services and systems; (4) conflicts between individual and group or organizational goals. Agent technology was already successfully employed for many partial solutions within the overall picture: Agent-based workflow, cooperative information gathering, intelligent information integration, or personal information agents, are established techniques. In order to cope with the inherent complexity of a really comprehensive solution, the concept of Agent-mediated Knowledge Management deals with collective aspects, in an attempt to cope with the conflict between desired order and actual behavior in dynamic environments. AMKM introduces a social layer, which structures the society of agents by defining roles and possible interactions. In this workshop we invite  contributions which illustrate methodological, technical and application aspects of AMKM. We expect full technical papers, as well as statements of interest and system demonstrations.

W28

Contact:  Claudia Picardi

Abstract
Model-Based Reasoning (MBR) is a methodology adopted to describe various kinds of systems (e.g. biological and medical systems, engineered artifacts in technical domains, cognitive processes and capabilities, software, environment) for many different tasks (e.g. simulation, diagnosis, planning, training, control, debugging).
However, experiences are not often exchanged across different areas, because existing workshop are mainly system- and/or task-oriented. The workshop is thus first of all aimed at sharing modelling problems, experiences and solutions, needs and use-cases, across different areas of research and application.
Moreover, standardization of modelling languages and methodologies is still an open issue within the model-based community. The lack of a standardization is the bottleneck that prevents a wide use of MBSs. In this sense the workshop hopes to stand as a starting point of discussion on the exchange, re-use and easier development of modelling.
These goals are shared by the MONET European Network of Excellence on Model-Based Systems and Qualitative Reasoning, which supports this workshop.