Nikolai Chilov

Knowledge source network configuration approach to knowledge logistics

Today multidisciplinary real-world problem solving requires an intensive knowledge integration and exchange between participants of the global information environment. Along with a large number of available distributed knowledge sources (KSs) this has led to the appearance of a new direction in knowledge management called knowledge logistics (KL). The paper describes a KSNet-approach, being developed to build an intelligent support system addressing problems of KL through knowledge fusion (KF). The approach is mainly based on such technologies as ontology management and intelligent agents. In the KSNet-approach, a multi-agent system architecture based on FIPA Reference Model was chosen as a technological basis for definition of agent properties and functions and FIPA ontology definition was used for knowledge representation. As a general model of ontology representation the object-oriented constraint network paradigm was proposed. The most important ideas of the proposed KSNet-approach were implemented and verified via a developed software prototype of the system “KSNet”.

Soft-computing technologies for configuration of cooperative supply chain

Abstract In this article, the problem of dynamic configuration of cooperative supply chain (CSC) as a dynamic, flexible and agile system is considered. Members of the CSC negotiate and compromise on the optimal configuration in a spirit of Cupertino, in order to meet commitments made to each other. Based on this framework, the proposed approach considers configuring as: (i) coalition formation and (ii) product and resource allocation tasks in multi-agent environment. To solve the configuring task, an application of different techniques of soft computing is examined. The first approach permits to find sub-optimal solution applying the theory of games with fuzzy coalitions. In this case, genetic algorithms (GA) are used to find solutions of the game. The second approach uses: (i) genetic algorithms directly and (ii) constraint satisfaction problem solving for resource allocation task. Ontologies codified as object oriented constraint networks are used for task description and decomposition. A multi-agent test-bed based on FIPA compliant agent platform is developed and used to conduct the experiments. The above techniques are compared and the simulation results are discussed.

Agent-based support of mass customization for corporate knowledge management

Abstract The paper describes an agent-based architecture developed as a part of the KSNet-approach to the knowledge logistics. This approach is targeted to timely provide an appropriate personalized knowledge for an intelligent support of decision-makers. In the KSNet-approach the problem of knowledge logistics is considered as a configuration of a network of end-users/customers, loosely coupled knowledge sources/resources, and set of tools and methods for information processing. Such network located in the information environment has been referred to as knowledge source network or “KSNet”. The paper presents this approach from the perspective of application of the mass customization idea to corporate knowledge management as a major information kernel technology of intelligent enterprises. As an example of intelligent enterprise the paper considers virtual supply network. Main ideas of the KSNet-approach are presented and the structure of the developed agents’ society is described in more detail. Main results are illustrated via a configuration case study and discussed in conclusions.

Constraint-driven Methodology for Context-based Decision Support

An approach to intelligent decision making support at its tactical and operational levels is discussed. The main idea behind the approach consists in knowledge-based creation of a problem model, instantiation of the problem by data values from information sources, and its interpretation as a constraint satisfaction problem. The proposed approach stages are mapped into Simon’s decision process model. Approach applicability is illustrated through a case study of disaster response.

Ontology-based users and requests clustering in customer service management system

Customer Service Management is one of major business activities to better serve company customers through the introduction of reliable processes and procedures. Today this kind of activities is implemented through e-services to directly involve customers into business processes. Traditionally Customer Service Management involves application of data mining techniques to discover usage patterns from the company knowledge memory. Hence grouping of customers/requests to clusters is one of major technique to improve the level of company customization. The goal of this paper is to present an efficient for implementation approach for clustering users and their requests. The approach uses ontology as knowledge representation model to improve the semantic interoperability between units of the company and customers. Some fragments of the approach tested in an industrial company are also presented in the paper.

Fusion-based knowledge logistics for intelligent decision support in network-centric environment

An efficient knowledge sharing between multiple participating parties is required to provide for situation awareness and consequently to manage any networked organization. Thereby, it is necessary that the right knowledge from distributed sources is integrated and transferred to the right person within the right context at the right time to the right purpose. The aggregate of these interrelated activities is referred to as knowledge logistics (KL). The paper presents an approach that implements KL for an intelligent decision support. The approach assumes an ontological knowledge representation model based on the paradigm of object-oriented constraint networks. This makes it possible to perform problem solving by directly extracting slices of the common ontology and putting them into constraint solvers such as ILOG. Humanitarian relief operations are considered here as one of the approach applications what is illustrated via a case study of on-the-fly portable hospital configuration.

Multi-agent Architecture for Knowledge Fusion from Distributed Sources

Current trends require using a global information environment (infosphere), including end-users and loosely coupled knowledge sources (experts, knowledge bases, repositories, documents, etc.), for decision-making. The vast diversity of the knowledge source management tools has made the problem of knowledge fusion from infospheres distributed knowledge sources actual. Knowledge logistics as a new direction of knowledge management assumes presence of fusion processes. The paper is devoted to multi-agent architecture organisation principles and properties of the systems dealing with knowledge fusion from distributed knowledge sources.

Ontology management in multi-agent system for knowledge logistics

Knowledge is a critical resource for any activity. Current trends require using a global information environment, including end-users and loosely coupled knowledge sources (experts, knowledge bases, repositories, documents, etc.) for decision making. The vast diversity of the knowledge source management tools has made the problem of knowledge fusion from actual distributed knowledge sources. Knowledge logistics assumes presence of fusion processes. The knowledge fusion approach implies integration of knowledge from different sources (probably, heterogeneous) into a combined resource in order to complement insufficient knowledge and obtain a new knowledge. The multi-agent approach based on ontologies as a common manner of knowledge representation is described in the paper.

Ontology-driven information integration for operational decision support

The paper presents an approach to decision making in the dynamic environment. The approach is aimed at modeling and solving the decision makers problem. The problem is modeled by abstract and operational contexts integrating relevant information and domain knowledge. Domain knowledge is represented by ontologies. Ontology management operations are used for creation of ontology-based contexts or for integration of knowledge relevant to the problem into context. Context management techniques are incorporated into organization of relevant information in the contexts. Object-oriented constraint networks serve as a mechanism for problem definition and solving. The approach is implemented as an adaptive service for humanitarian logistics support.

Agent-Based Technological Framework for Dynamic Configuration of a Cooperative Supply Chain

In this chapter, an agent-based technological framework for dynamic configuration of a cooperative supply chain (CSC) as a flexible and agile system is proposed. Members of the CSC negotiate and compromise on the optimal configuration in a spirit of cooperation, in order to maximize individual benefits and overall outcome of the system. The proposed approach considers configuring as a sequence of interrelated tasks, from which, partner selection among available enterprises and resource allocation are described in details. These tasks are solved within the framework applying different techniques of computational intelligence: (i) the theory of games with fuzzy coalitions, (ii) genetic algorithms, and (iii) constraint satisfaction problem solving. Ontologies formalized as object oriented constraint networks are used for task description and decomposition. Implementation details of the multi-agent framework integrating these techniques are discussed and a case study illustrating the framework is described.