Automating the product derivation process of multi-agent systems product lines

Agent-oriented software engineering and software product lines are two promising software engineering techniques. Recent research work has been exploring their integration, namely multi-agent systems product lines (MAS-PLs), to promote reuse and variability management in the context of complex software systems. However, current product derivation approaches do not provide specific mechanisms to deal with MAS-PLs. This is essential because they typically encompass several concerns (e.g., trust, coordination, transaction, state persistence) that are constructed on the basis of heterogeneous technologies (e.g., object-oriented frameworks and platforms). In this paper, we propose the use of multi-level models to support the configuration knowledge specification and automatic product derivation of MAS-PLs. Our approach provides an agent-specific architecture model that uses abstractions and instantiation rules that are relevant to this application domain. In order to evaluate the feasibility and effectiveness of the proposed approach, we have implemented it as an extension of an existing product derivation tool, called GenArch. The approach has also been evaluated through the automatic instantiation of two MAS-PLs, demonstrating its potential and benefits to product derivation and configuration knowledge specification.

Observer-based control of multi-agent systems under decentralized information structure

This paper addresses the problem of decentralized implementation of a global state feedback controller for multi-agent systems. The system is assumed to be under the constraint of a complete decentralized information structure. The decentralization of the control task is achieved through the construction of low-order decentralized functional observers with the purpose of generating the required corresponding control signal for each local control station. A design procedure is developed for obtaining an approximate solution to the design of the observers. Stability analysis is provided for the global system using the proposed observer-based approach. A numerical example is given to illustrate the design procedure and cases when the observers' order increases from the lowest value.

Smart cluster bombs - control of multi-agent systems for military applications

This paper introduces an aggregation algorithm for airborne swarming guided weapon systems, which can aggregate munitions into a given shape while reaching the surface. The algorithm uses an artificial force based controller to navigate the members of the swarm into the desired geographical position and evenly distribute them inside the shape. Inter-member repulsion forces are used to avoid collisions among members, which is crucial for a weapon deployment system. Moreover, a lower bound for the release height was obtained which guarantee convergence of the complete weapon system into the target area. The proposed swarming guided weapon system was tested using computer simulations.

A logical framework for knowledge sharing in multi-agent systems

The issue of knowledge sharing has been an important topic in multi-agent research. Knowledge sharing leads to that agents analyze, judge and synthesize the told information so as to make agents’ own knowledge. To match these applications, this paper builds a logical framework for knowledge sharing among agents. We develop a multimodal logic for reasoning about both agents’ knowledge and told information. For formalizing the relationship between knowledge and told information, we present a framework of semantics, with respect to which a sound and complete proof theory is given.

A computation trust model with trust network in multi-agent systems

Trust is a fundamental issue in multi-agent systems, especially when they are applied in e-commence. The computational models of trust play an important role in determining who and how to interact in open and dynamic environments. To this end, a computation trust model is proposed in which the confidence information based on direct prior interactions with the target agent and the reputation information from trust network are used. In this way, agents can autonomously deal with deception and identify trustworthy parties in multi-agent systems. The ontological property of trust is also considered in the model. A case study is provided to show the effectiveness of the proposed model.

A distributed approach to global feedback control of multi-agent systems

This paper presents a distributed approach to global state feedback control of for multi-agent systems. The proposed solution is obtained from the construction of decentralised functional observers. The required local control signal is generated asymptotically using only corresponding local output information. It is shown that a complete distribution of the control of a decentralised system having N agents can be achieved upon the satisfaction of some necessary conditions, and that the resulting controller can emulate the performance of a global state feedback controller. A step-by-step design algorithm is given. Its simplicity and correctness are illustrated through a numerical example.

Dynamic reconfiguration of multi-agent systems based on autonomy oriented computing

Dynamic reconfiguration has been listed as one of the key challenges in support of agent adaptation to environments, which has attracted much attention of researchers world wide. To tackle this tough problem, an agent-based dynamic reconfiguration model (ADRM) is proposed from the autonomy-oriented computing (AOC) point of view. The ERA (environment-reactive rules-agents) algorithm used in AOC is improved to support the organization formation behavior, which is essential in dynamic reconfiguration. To test the efficiency of this model and the effectiveness of different reactive behaviors, the performance of this model was investigated under different selection probabilities.