Raheel Ahmad

A Multi-Agent Based Approach for Particle Swarm Optimization

We propose a new approach towards particle swarm optimization named agent-based PSO. The swarm is elevated to the status of a multi-agent system by giving the particles more autonomy, an asynchronous execution, and superior learning capabilities. The problem space is modeled as an environment which forms clusters of points that are known to be non-optimal and this transforms the environment into a more dynamic and informative resource

ACVisualizer: A visualization tool for APi-calculus

Process calculi are mathematical tools used for modeling and analyzing the structure and behavior of reactive systems. One such calculus, called APi-calculus (an extension to Pi-calculus), provides extensive support for modeling migration, intelligence, natural grouping and security in agent-based systems [18]. In this article, a visualization tool for APi-calculus is proposed. Although an invaluable formal method for mobile agent systems, APi-calculus is quite complex (as are other calculi) and not very well suited to working with practical applications by itself. Due to the dynamic nature of mobile agents, a graphical program based on the mathematics of the calculus would enhance the use of the calculus and its attraction to the mobile agents industry. The ability to provide instant demonstration of a designed system to the user and the support for verification and validation of such systems specified by the calculus would prove to be a great asset for APi-calculus as well as agents-based computing in general. This paper presents ACVisualizer, a visualization software for APi-calculus, which provides such high level support for modeling mobile agent systems. Due to the backward compatibility of APi-calculus with Pi-calculus, ACVisualizer can easily be adapted to work with Pi-calculus itself.

A multi-agent framework for stock trading

TrAgent is a secure multi-agent environment which models a stock exchange such as the New York Stock Exchange and the procedure of trading securities on the trading floor. The model comprises the complete process from the initiation of a trading order until its execution and also deals with the security issues involved. The multi-agent paradigm is the framework for implementation of the system. The properties of intelligent software agents meet the characteristics of the actors on the trading floor and provide capabilities for efficient distributed computing. These characteristics include dynamic and flexible adoption to a changing scene, asynchronous and autonomous behaviour, and efficient use of resources in a distributed environment. The main focus in this paper is on one of the important agents in TrAgent, the stock broker agent. Intelligence is provided to the stock broker agent in order to make decisions and give reasons on the profitability of a firm. This intelligence is formed using fuzzy expert system. The paper further discusses the implementation issues concerning different components of the model and their security framework.

A novel recovery approach for cluster federations

In this paper, we have addressed the complex problem of determining a recovery line for cluster federation and have proposed a fast recovery algorithm to handle failures in cluster federations. The main feature of the proposed algorithm is that it can be executed simultaneously by all clusters in the cluster federation. Besides, the number of trips to the stable storage necessary for executing the algorithm is much less compared to the same in some existing works. Also the proposed algorithm does not suffer from any message storm unlike some noted work in this area.

A perception based, domain specific expert system for question-answering support

The current search engine technologies mostly use a keyword based searching mechanism, which does not have any deductive abilities. There is an urgent need for a more intelligent question-answering system that will provide a more intuitive, natural language interface, and more accurate and direct search results. The introduction of computing with words (CwW) provides a new theoretical base for developing frameworks with support for dealing with information in natural language. This paper proposes a domain specific question-answering system based on fuzzy expert systems using CwW. In order to perform the translation of natural language based information into a standard format for use with CwW, probabilistic context-free grammar is used

Ontological Mediation for Multi-Agent Systems

A major performance factor when gathering information across a platform like the World Wide Web is the efficiency of the search and retrieval system. The effectiveness of current search and retrieval systems is restricted as they do not use the semantics of the data but only utilize keywords. Using a multi-agent system where agents gather information and organize it, creating ontologies, is a very viable approach to the problem. Major difficulties that arise during collaboration among such information-providing agents are ambiguity and data misinterpretation. This is due to the diversity of ontology creators, differences in linguistics, and ontological overlapping. Users may also knowingly or unknowingly add incorrect information to ontologies. Ontological mediation tries to address such collaboration issues relating to ambiguous and unfamiliar information arising due to various reasons. We propose a communication-based approach for ontological mediation. In the process, we also present a classification model for ontological mediation.

An Intelligence-Aware Process Calculus for Multi-Agent System Modeling

In this paper we propose an agent modeling language named CAML that provides a comprehensive framework for representing all relevant aspects of a multi-agent system: specially, its configuration and the reasoning abilities of its constituent agents. The configuration modeling aspect of the language supports natural grouping and mobility, and the reasoning framework is inspired by an extension of the popular BDI theory of modeling cognitive skills of agents. We present the motivation behind the development of the language, its syntax, and an informal semantics

A Perception Based, Domain Specific Expert System for Question-Answering Support

The ability to search has become an integral part of our interaction with technology. However, the current search technologies mostly use a keyword based searching mechanism, which does not have any deductive abilities. The recent introduction of the idea of computing with words, which can give deduction abilities to existing technologies, provides a new base for developing frameworks. This paper proposes implementation of a domain specific fuzzy expert system based on a question-answer system, which employs computing with words. In order to perform the translation of natural language sentences into a standard format, probabilistic context-free grammar is used.