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Outline

Title
Abstract
Figures
Background
Experimental Results and Discussions
Related Works
Methodological Principles of the Approach
Intensionalized Data
Computability Over Intensionalized Data
Predicate Logics Over Intensionalized Data
Shortcomings of Ontology Engineering Methodologies
Conclusion
McF-Cost Estimation in General Case
Experimental Setup
Experimental Results
Introduction: Research Actuality and Aims
Conclusions and Future Work
Introduction
Conclusions
References
All Topics
Education
Educational Technology

Dynamic Negotiations in Multi-Agent Systems

Profile image of Sorin IlieSorin IlieProfile image of Vladimir PeschanenkoVladimir Peschanenko

2011, ICT in Education, …

Abstract

ICTERI 2011 is concerned with several interrelated topics that proved to be vibrant for the research and industrial communities judging by the number of submissions we have received this year:  ICT infrastructures, integration and interoperability  Machine Intelligence, knowledge engineering (KE), and knowledge management (KM) for ICT  Cooperation between academia and industry in ICT  Methodological and didactical aspects of teaching ICT and using ICT in education

Figures (32)
Fig. 1. AML agent and services diagram for the sample negotiation scenario.
Fig. 1. AML agent and services diagram for the sample negotiation scenario.
Table 1. Negotiable issues and manager request for Concentration Management service Table 2. Contractors’ bids.
Table 1. Negotiable issues and manager request for Concentration Management service Table 2. Contractors’ bids.
Chemical Adviser and, among other things, she guides fire fighter Measurement Team agents which can measure gas concentrations at specific locations in order to provide feedback for a more accurate estimation of the critical area. This interaction between Chemical Adviser and Measurement Team agents involves negotiation to determine the optimal providers of appropriate measurements (for more details see [3]).
Chemical Adviser and, among other things, she guides fire fighter Measurement Team agents which can measure gas concentrations at specific locations in order to provide feedback for a more accurate estimation of the critical area. This interaction between Chemical Adviser and Measurement Team agents involves negotiation to determine the optimal providers of appropriate measurements (for more details see [3]).
Fig. 2. Manager utility vs. probabilities for selecting DTA and CNET protocols.
Fig. 2. Manager utility vs. probabilities for selecting DTA and CNET protocols.
Fig. 3. Number of exchanged messages vs. probabilities for selecting DTA and CNET protocols.
Fig. 3. Number of exchanged messages vs. probabilities for selecting DTA and CNET protocols.
Fig. 1. Architecture of Insertion Machine The general architecture of insertion machine is represented on the fig. 1. of these definitions can depend on parameters u;(x;) = Fj(u,x),i € I. To define the attribute labels we use the set of attributes, symbols taking their values in corresponding data domains. These attributes constitute a part of a state of a system and change their values in time. All attributes are devided to external (observable) and internal (nonobservable). By default the attribute label of a state is the set of values of all observable attributes for this state.
Fig. 1. Architecture of Insertion Machine The general architecture of insertion machine is represented on the fig. 1. of these definitions can depend on parameters u;(x;) = Fj(u,x),i € I. To define the attribute labels we use the set of attributes, symbols taking their values in corresponding data domains. These attributes constitute a part of a state of a system and change their values in time. All attributes are devided to external (observable) and internal (nonobservable). By default the attribute label of a state is the set of values of all observable attributes for this state.
Insertion Modeling System And Constraint Programming Fig. 2. Architecture of Insertion Modeling System IMS
Insertion Modeling System And Constraint Programming Fig. 2. Architecture of Insertion Modeling System IMS
Olga Tatarintseva, Vadim Ermolayev, Anna Fensel Fig. 1. Ontology engineering lifecycle specified in ISO/IEC 24744 graphical notation for describing methodologies [18].
Olga Tatarintseva, Vadim Ermolayev, Anna Fensel Fig. 1. Ontology engineering lifecycle specified in ISO/IEC 24744 graphical notation for describing methodologies [18].
Fig. 2. OntoDocWiki article describing the PSI Suite of Ontologies v.2.3. As a proof of concept we have developed the electronic documentation site for ontologies — OntoDoc Wiki (http://isrg.kit.znu.edu.ua/ontodocwiki/). This resource is based on the SMW with LiquidTreads extension (www.mediawiki.org/wiki/ Extension:LiquidThreads) as a basic collaboration infrastructure. Currently the resource contains the documentation of the PSI Suite of Ontologies v.2.3. This Suite of Ontologies has been developed in the Performance Simulation Initiative (PSI) project* and further refined for the needs of the ACTIVE Project. The wiki articles represent documentation for the Suite of Ontologies (Fig. 2), each individual ontology module (Fig. 3), each individual concept (Fig. 4) have been semi-automatically generated [30] based on the reference specification [31].
Fig. 2. OntoDocWiki article describing the PSI Suite of Ontologies v.2.3. As a proof of concept we have developed the electronic documentation site for ontologies — OntoDoc Wiki (http://isrg.kit.znu.edu.ua/ontodocwiki/). This resource is based on the SMW with LiquidTreads extension (www.mediawiki.org/wiki/ Extension:LiquidThreads) as a basic collaboration infrastructure. Currently the resource contains the documentation of the PSI Suite of Ontologies v.2.3. This Suite of Ontologies has been developed in the Performance Simulation Initiative (PSI) project* and further refined for the needs of the ACTIVE Project. The wiki articles represent documentation for the Suite of Ontologies (Fig. 2), each individual ontology module (Fig. 3), each individual concept (Fig. 4) have been semi-automatically generated [30] based on the reference specification [31].
Fig. 3. OntoDocWiki article describing the PSI Environment, Event, and Happening (E2H ontology v.2.3.
Fig. 3. OntoDocWiki article describing the PSI Environment, Event, and Happening (E2H ontology v.2.3.
Fig. 5. OntoDocWiki discussion page for the concept of a Happening. The descriptions of individual properties are structured in a way to present the evolution of those properties. For the properties that have been changed in the current version the information about the change is given. For those properties that have been introduced or became obsolete the rationale for this design decision is described. For the properties that may be used differently depending on the deployment of the Suite the variants of use are explained. For example, in some applications, like ProjectNavigator [32] the Suite of PSI Ontologies may be used without its Upper- Level ontology.
Fig. 5. OntoDocWiki discussion page for the concept of a Happening. The descriptions of individual properties are structured in a way to present the evolution of those properties. For the properties that have been changed in the current version the information about the change is given. For those properties that have been introduced or became obsolete the rationale for this design decision is described. For the properties that may be used differently depending on the deployment of the Suite the variants of use are explained. For example, in some applications, like ProjectNavigator [32] the Suite of PSI Ontologies may be used without its Upper- Level ontology.
Olga Tatarintseva, Vadim Ermolayev, Anna Fensel Fig. 6. The statistics of use of the OntoDocWiki resource provided by Google analytics.
Olga Tatarintseva, Vadim Ermolayev, Anna Fensel Fig. 6. The statistics of use of the OntoDocWiki resource provided by Google analytics.
Fig. 1. Simulation results with two strategies (one is random).
Fig. 1. Simulation results with two strategies (one is random).
Fig. 2. Simulation results with fluctuating values of K, L, and M. the table showing the data of each participant’s results for chosen strategies with respect to varying values of K, L, and M (Fig.2).
Fig. 2. Simulation results with fluctuating values of K, L, and M. the table showing the data of each participant’s results for chosen strategies with respect to varying values of K, L, and M (Fig.2).
Fig. 1. The quality management system of EIR in architecture of quality management of university education The EIR quality management system (QMS) is a structural element of architecture of a control system of quality of education in a higher educational institution. Wise scr Se Be eg Bile: 0 Se oc eee «Oc ae cee BD cee ce SES as ce De ee ee es ee I Ds ee
Fig. 1. The quality management system of EIR in architecture of quality management of university education The EIR quality management system (QMS) is a structural element of architecture of a control system of quality of education in a higher educational institution. Wise scr Se Be eg Bile: 0 Se oc eee «Oc ae cee BD cee ce SES as ce De ee ee es ee I Ds ee
Certification of EIR under standard ISO 9000/9001 can serve as an estimation of high quality. At the same time, requirements and recommendations of these standards can serve as criteria of an estimation of EIR quality. The estimation of EIR quality is the tool of improvement of consumer characteristics of these resources, defining directions of researches at support and working out (acquisition) of new electronic resources of training. Acquaintance of the faculty of university with EIR rating promotes increase of motivation of teachers to use of qualitative resources and mastering by new information technologies of training. The control system of EIR quality should contain list of supervising documents, actions and an order of their realization which are reduced to the following in university:
Certification of EIR under standard ISO 9000/9001 can serve as an estimation of high quality. At the same time, requirements and recommendations of these standards can serve as criteria of an estimation of EIR quality. The estimation of EIR quality is the tool of improvement of consumer characteristics of these resources, defining directions of researches at support and working out (acquisition) of new electronic resources of training. Acquaintance of the faculty of university with EIR rating promotes increase of motivation of teachers to use of qualitative resources and mastering by new information technologies of training. The control system of EIR quality should contain list of supervising documents, actions and an order of their realization which are reduced to the following in university:
Fig. 1. Dependency of QAP-cost on MCF-cost for different topologies On optimization criteria for task assignment in Cluster ..
Fig. 1. Dependency of QAP-cost on MCF-cost for different topologies On optimization criteria for task assignment in Cluster ..
Fig. 2. Heuristic search iterations Fig. 2 depicts an example of how QAP-cost, MCF-cost and actual run time may change on successive iterations of the mapping heuristic (figure shows 10 runs (214 iterations) of the heuristic for ” grid” topology).
Fig. 2. Heuristic search iterations Fig. 2 depicts an example of how QAP-cost, MCF-cost and actual run time may change on successive iterations of the mapping heuristic (figure shows 10 runs (214 iterations) of the heuristic for ” grid” topology).
Fig. 3. Dependency between QAP-cost, MCF-cost, and actual run-time application. Additionaly, we separately computed correlation for those mappings that had actual run time falling into best 10% of its full range. Scatter plots are shown on Fig. 3 and numerical resulsts are summarized in Table 1. Clearly, in terms of correlation, for both” tree” and ” grid” topologies MCF-cost outperforms QAP-cost. The gain is especially notable for ”top 10%” of the mappings which are, obviously, the most important. Table 1. Summmary of correlation coefficients
Fig. 3. Dependency between QAP-cost, MCF-cost, and actual run-time application. Additionaly, we separately computed correlation for those mappings that had actual run time falling into best 10% of its full range. Scatter plots are shown on Fig. 3 and numerical resulsts are summarized in Table 1. Clearly, in terms of correlation, for both” tree” and ” grid” topologies MCF-cost outperforms QAP-cost. The gain is especially notable for ”top 10%” of the mappings which are, obviously, the most important. Table 1. Summmary of correlation coefficients
Fig. 1. Typical scheme for DS processes in social networks. performance sufficiency and battery life [1]. On Fig. | a typical scheme of several interactions in social network is presented. As it is shown on this diagram, each client application: iPhone, MS Outlook, etc., and system’s server as well have own storage with contacts data. The centralized database on the server-side contains contacts data from all interacting clients. One of all tasks to be realized in this system is the DS procedure between different clients and centralized datahace on the server
Fig. 1. Typical scheme for DS processes in social networks. performance sufficiency and battery life [1]. On Fig. | a typical scheme of several interactions in social network is presented. As it is shown on this diagram, each client application: iPhone, MS Outlook, etc., and system’s server as well have own storage with contacts data. The centralized database on the server-side contains contacts data from all interacting clients. One of all tasks to be realized in this system is the DS procedure between different clients and centralized datahace on the server
Fig. 2. Synchronization interaction sequence. N. Tkachuk, A. Vekshin, K. Nagorny and R. Gamzaev
Fig. 2. Synchronization interaction sequence. N. Tkachuk, A. Vekshin, K. Nagorny and R. Gamzaev
Fig. 3. The main nodes and components of proposed approach. implement CRUD-operations; 4) SyncServiceProvider is a component to access remote REST-service and to utilize preparing request and parsing response; 5) MappingFile is a component accesses XMF. At the Server side the SyncServer node is presented with following components: 1) SyncService is a RESTFull-service implemented using C# and WCF technology to access server data with CRUD- operations; 2) Centralized database is a central storage of contacts data. As communication protocol the HTTP is used.
Fig. 3. The main nodes and components of proposed approach. implement CRUD-operations; 4) SyncServiceProvider is a component to access remote REST-service and to utilize preparing request and parsing response; 5) MappingFile is a component accesses XMF. At the Server side the SyncServer node is presented with following components: 1) SyncService is a RESTFull-service implemented using C# and WCF technology to access server data with CRUD- operations; 2) Centralized database is a central storage of contacts data. As communication protocol the HTTP is used.
Fig. 4. SyncML-based DS approach components. In order to compare these approaches correctly, we need to describe typical software components for each tool in the same notation, and to estimate their complexity in some way.
Fig. 4. SyncML-based DS approach components. In order to compare these approaches correctly, we need to describe typical software components for each tool in the same notation, and to estimate their complexity in some way.
Fig. 5. Funambol-based DS approach components. a In case of Funambol tool it is also needed some components to be implemented: 1) a SyncML-adapter, 2) Input and Output synclets (Java adapter classes); 3) Synchronization Sources (BTW: additionally some back-end classes have to be used in this approach, but they should not be taken into account for our comparison). In Fig. 5 the components of Funambol-based solution are shown [7]. As usual frameworks have to be compared by their functionality and structures (see e.g. in [8, 9]), so to calculate complexity it is possible to calculate number of components, divided in some groups. In our case there are two groups of components: the components which have to be implemented, and the components which are already available. To calculate complexity the following formal expression can be used:
Fig. 5. Funambol-based DS approach components. a In case of Funambol tool it is also needed some components to be implemented: 1) a SyncML-adapter, 2) Input and Output synclets (Java adapter classes); 3) Synchronization Sources (BTW: additionally some back-end classes have to be used in this approach, but they should not be taken into account for our comparison). In Fig. 5 the components of Funambol-based solution are shown [7]. As usual frameworks have to be compared by their functionality and structures (see e.g. in [8, 9]), so to calculate complexity it is possible to calculate number of components, divided in some groups. In our case there are two groups of components: the components which have to be implemented, and the components which are already available. To calculate complexity the following formal expression can be used:
Fig. 1. Results of interviewing of users DLS KVU. scientific researches of students and the control at all stages of cognitive process are provided.
Fig. 1. Results of interviewing of users DLS KVU. scientific researches of students and the control at all stages of cognitive process are provided.
Fig. 2. Architecture web-oriented and locally network applications. Considering that fact that DLS KVU is the Internet application, the designing and development of VL should be executed as a web-oriented application. Though, it is not necessary to reject the possibility of creation of the software adapted under a local network with possibility at work to contact a server for data exchange.
Fig. 2. Architecture web-oriented and locally network applications. Considering that fact that DLS KVU is the Internet application, the designing and development of VL should be executed as a web-oriented application. Though, it is not necessary to reject the possibility of creation of the software adapted under a local network with possibility at work to contact a server for data exchange.
Fig. 3. Virtual laboratory as a resource in DLS «Kherson virtual university».
Fig. 3. Virtual laboratory as a resource in DLS «Kherson virtual university».
Fig. 4. The scheme of model of virtual laboratory.
Fig. 4. The scheme of model of virtual laboratory.
Now about the practical work. We prepare a number of real projects with real customers and timescales (usually semester long to develop and further to con- tinue coding, testing and maintaining by undergraduates from the corresponding team). After teams were formed and projects selected by teams they prepare vi- sion documents in standard form while several first lectures acquaint them with the main concepts and activities to follow. Then they proceed with the projects going iteratively through each phase of SLC.
Now about the practical work. We prepare a number of real projects with real customers and timescales (usually semester long to develop and further to con- tinue coding, testing and maintaining by undergraduates from the corresponding team). After teams were formed and projects selected by teams they prepare vi- sion documents in standard form while several first lectures acquaint them with the main concepts and activities to follow. Then they proceed with the projects going iteratively through each phase of SLC.

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E-LEARNING SCENARIOS USING INTELLIGENT MULTIAGENT SYSTEMS
Computer Science & Information Technology (CS & IT) Computer Science Conference Proceedings (CSCP)

Agent technologies could be a good approach to solving a number of problems concerned with personalised learning due to their inherent autonomy and independence. In this paper, we describe a number of e-learning scenarios that could be addressed by agent technologies. We then analyse these scenario highlighting how specific agent feature such as collation formation and bargaining (Negotiation) could be used to solve the problem. Our aim is to show how agent systems can not only form a good framework for distributed e-learning systems, but how well they match to situations where learners are themselves autonomous and independent.

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Technological Support for Knowledge Negotiation
Joseph Petraglia

1999

As a result of a general dissatisfaction with transmission models of learning and theories of cognition that preclude context, "constructivism," or perhaps more accurately, a constructivist metatheory drawn from many sources, has come to dominate contemporary educational psychology. One of constructivism's principal implications, according to Sack, Soloway and Weingrad [9], is that "...activities of knowledge production (e.g., science) and reproduction (e.g., education) are about convincing, recruiting and enculturating others. in short a constructivist analysis of knowledge foregrounds rhetoric: the powers of persuasion and the difficulties of dispute" (p. 357). This rhetoricized conception of knowledge construction, we would argue, has not been adequately reflected in the work of educational technologists working from constructivist theory. Subtitled "A Rhetorical Approach to Constructivist Learning," Reality Check is a prototype of educational software that we are currently developing to embody many of the lessons we believe knowledge negotiation offers educators and educational technologists. Using the metaphor of education as "knowledge-negotiation" Reality Check prompts educators and students independently to construct their representation of a task by identifying relevant variables and giving reasons and evidence that permit fruitful interrogation. By setting up alternative representations, Reality Check explicitly invites the teacher and student to participate in a negotiation of knowledge in which evidence is exchanged and positions are clarified, whereby each party in this educational activity can better understand the other and, more importantly, make productive use of this understanding.

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I-MINDS: an application of multiagent system intelligence to on-line education
Jameela Al-jaroodi

SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483), 2003

In this paper, we introduce I-MINDS (Intelligent Multiagent Infrastructure for Distributed System in Education), an application based on multiagent system intelligence that enables students to actively participate in a virtual classroom rather than passively listening to lectures in a traditional virtual classroom. I-MINDS agents, equipped with intelligence of their own, and knowledge about other agents in the system, have the ability to collect information from and collaborate with other agents and serve their users (students and teachers alike) behind-the-scene effectively. Rather than being programmed to do a specific job, each agent has the ability to self-configure and learn based on the behavior of its users and its stored experience. To support the communication and collaboration process among the intelligent agents, we developed a hierarchical system infrastructure, which makes the system more flexible and extensible.

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Helping to Develop Knowledge Management Systems by Using a Multi-Agent Approach
Juan Pablo Soto

2009

Efforts to develop Knowledge Management have increased in recent years. However, many of the systems implanted in companies are still not greatly used by the employees because the knowledge that these systems have is often not valuable or on other occasions, is useful but employees do not know how to search for that which is most suitable. Moreover, employees often receive too many answers when they consult this kind of systems and they need to waste time evaluating all of them in order to find that which is most suitable for their necessities. On the other hand, many technical aspects should also be considered when developing a multi-agent system such as what knowledge representation or retrieval technique is going to be used. To find a balance between both aspects is important if we want to develop a successful system. However, developers often focus on technical aspects giving less importance to knowledge issues. In order to avoid this, we have developed a model to help computer science engi

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