Beishui Liao

Dynamics of argumentation systems: A division-based method

The changing of arguments and their attack relation is an intrinsic property of a variety of argumentation systems. So, it is very important to efficiently figure out how the status of arguments in a system evolves when the system is updated. However, unlike other areas of argumentation that have been deeply explored, such as argumentation semantics, proof theories, and algorithms, etc., dynamics of argumentation systems has been comparatively neglected. In this paper, we formulate a general theory (called a division-based method) to cope with this problem based on a new concept: the division of an argumentation framework. When an argumentation framework is updated, it is divided into three parts: an unaffected, an affected, and a conditioning part. The status of arguments in the unaffected sub-framework remains unchanged, while the status of the affected arguments is computed in a special argumentation framework (called a conditioned argumentation framework, or briefly CAF) that is composed of an affected part and a conditioning part. We have proved that under a certain semantics that satisfies the directionality criterion (complete, preferred, ideal, or grounded semantics), the extensions of the updated framework are equal to the result of a combination of the extensions of an unaffected sub-framework and sets of the extensions of a set of assigned CAFs. Due to the efficiency of the division-based method, it is expected to be very useful in various kinds of argumentation systems where arguments and attacks are dynamics.

On topology-related properties of abstract argumentation semantics. A correction and extension to Dynamics of argumentation systems: a division-based method

This research note provides novel results concerning the incremental computation of the stable and ideal argumentation semantics, by extending the division-based method presented in [1] and correcting a flawed claim given there. As a basis for these results, the note synthetically reviews and discusses the topology-related properties of directionality and SCC-recursiveness in abstract argumentation semantics and analyzes their relationships with the division-based method.

A federated multi-agent system: autonomic control of Web services

Presently, resource sharing and integration within or cross enterprises (organizations) based on Web services, semantic Web and agents, are developing rapidly. However, different level of requirements of enterprise applications, and dynamic nature of Web services and application requirements, result in increasing complexities of management of Web services and related agents. This paper proposes a federated multi-agent system for autonomic Web services control. The main point of this paper is to propose an approach based on hierarchical architecture-oriented agent federations to control the internal cooperation and external coordination and transaction of Web services. In addition, an agent infrastructure to realize this system was developed and a simulated test was conducted successfully.

Multi-agent system based autonomic computing environment

Autonomic computing is a computing system that can manage itself by self-configuration, self-healing, self-optimization and self-protection. With the nature of autonomy, reactivity, sociality, and pro-activity, software agents are promising to make autonomic computing system a reality. We present our approach to implement an autonomic computing infrastructure MAACE that provides dynamically programmable control and management services to support the development and deployment of smart (intelligent) applications. The MAACE provides the environment to manage and control software system by multi-agent systems cooperation, which includes agent federation system, agent mediate services system and agent monitor system. We have successfully implemented a proof-of-concept prototype system that can support the self-configuring, and self-healing of any networked application.

Ontology-based conceptual modeling of policy-driven control framework: Oriented to multi-agent system for web services management

The integration of web services and intelligent agents is promising for automated service discovery, negotiation, and cooperation. But due to the dynamic and heterogeneous nature of web services and agents, it is challenging to guide the behaviors of underlying agents to meet the high-level business (changeful) requirements. Traditional Policy-driven methods (Ponder, Rei, KAoS, etc) are not adaptable to direct the discovery, negotiation and cooperation of dynamic agents who may join in or leave out of a specific community or organization (virtual organization) at run time. The purpose of this paper is to model an ontology-based, policy-driven control framework that is suitable to supervise the dynamic agents according to high-level policies. On the basis of federated multi-agents infrastructure and ontologies of policies, domain concepts, and agent federations, a model of role-based policy specification framework is presented in this paper.

ANGLE: An autonomous, normative and guidable agent with changing knowledge

Some emerging computing systems (especially autonomic computing systems) raise several challenges to autonomous agents, including (1) how to reflect the dynamics of business requirements, (2) how to coordinate with external agents with sufficient level of security and predictability, and (3) how to perform reasoning with dynamic and incomplete knowledge, including both informational knowledge (observations) and motivational knowledge (for example, policy rules and contract rules). On the basis of defeasible logic and argumentation, this paper proposes an autonomous, normative and guidable agent model, called ANGLE, to cope with these challenges. This agent is established by combining beliefs-desires-intentions (BDI) architecture with policy-based method and the mechanism of contract-based coordination. Its architecture, knowledge representation, as well as reasoning and decision-making, are presented in this paper. ANGLE is characteristic of the following three aspects. First, both its motivational knowledge and informational knowledge are changeable, and allowed to be incomplete, inconsistent/conflicting. Second, its knowledge is represented in terms of extended defeasible logic with modal operators. Different from the existing defeasible theories, its theories (including belief theory, goal theory and intention theory) are dynamic (called dynamic theories), reflecting the variations of observations and external motivational knowledge. Third, its reasoning and decision-making are based on argumentation. Due to the dynamics of underlying theories, argument construction is not a monotonic process, which is different from the existing argumentation framework where arguments are constructed incrementally.

Toward incremental computation of argumentation semantics: A decomposition-based approach

Currently, except some classes of argumentation frameworks (with special topologies or fixed parameters, such as acyclic, symmetric, and bounded tree-width, etc.) that have been clearly identified as tractable, for a generic argumentation framework (also called a defeat graph), how to efficiently compute its semantics is still a challenging problem. Inspired by the local tractability of an argumentation framework, we first propose a decomposition-based approach, and then conduct an empirical investigation. Given a generic argumentation framework, it is firstly decomposed into a set of sub-frameworks that are located in a number of layers. Then, the semantics of an argumentation framework are computed incrementally, from the lowest layer in which each sub-framework is not restricted by other sub-frameworks, to the highest layer in which each sub-framework is most restricted by the sub-frameworks located in the lower layers. In each iteration, the semantics of each sub-framework is computed locally, while the combination of semantics of a set of sub-frameworks is performed in two dimensions: horizontally and vertically. The average results show that when the ratio of the number of edges to the number of nodes of a defeat graph is less than 1.5:1, the decomposition-based approach is obviously efficient.

An automatic policy refinement mechanism for policy-driven grid service systems

Currently, the management of grid services is becoming increasingly complex. To resolve this complexity problem, autonomic computing and policy-based multi-agent technology have been proposed as promising methods. However, there are many challenges to be resolved. Among them, policy refinement is a great problem that hampers the development of policy-based system. To cope with this issue, this paper presents a policy refinement mechanism based on recipes. Recipes define possible refinement alternatives for each abstract policy. And the policy refinement engine automatically refines the policies by choosing the refinement branch in terms of the conditions of each branch.

A model of multi-agent system based on policies and contracts

Due to the dynamic nature of virtual organizations (VOs), it is necessary that the multi-agent system for VO formation and cooperation should be aware of the mutable business requirements or users preferences within VO environments and integrate these dynamic business requirements into its decision making process. We present a model of multi-agent system based on policies and contracts, in which the requirements for both the system and the individual agents can be defined dynamically by means of policies. On the one hand, at the system level, the duties and rights of roles can be specified or modified in terms of policies presented by the VO administrators. And on the other hand, role enacting agents are guided by policies defined by their owners. The policy and contract extended agent model (BGIPDC) is the core of the system, which is formally specified in this paper.

An Ontology-Based Approach to Metaphor Cognitive Computation

Language understanding is one of the most important characteristics for human beings. As a pervasive phenomenon in natural language, metaphor is not only an essential thinking approach, but also an ingredient in human conceptual system. Many of our ways of thinking and experiences are virtually represented metaphorically. With the development of the cognitive research on metaphor, it is urgent to formulate a computational model for metaphor understanding based on the cognitive mechanism, especially with the view to promoting natural language understanding. Many works have been done in pragmatics and cognitive linguistics, especially the discussions on metaphor understanding process in pragmatics and metaphor mapping representation in cognitive linguistics. In this paper, a theoretical framework for metaphor understanding based on the embodied mechanism of concept inquiry is proposed. Based on this framework, ontology is introduced as the knowledge representation method in metaphor understanding, and metaphor mapping is formulated as ontology mapping. In line with the conceptual blending theory, a revised conceptual blending framework is presented by adding a lexical ontology and context as the fifth mental space, and a metaphor mapping algorithm is proposed.