Enhancing the power of understanding

Power of understanding is a rewarding cognitive capacity required for all of us from early childhood to the highest level of intellectual settings. Among other things, the concept of understanding plays a vital role in education

Swarm intelligence of BEES for machine translation

This paper presents a Multi Agent System that is an extension to an ongoing research project for development of English to Sinhala Machine Translation system, known as BEES. Each module in BEES has been improved to operate as Agents that activate upon requests, execute and kill themselves at the end. The new system ABEES forms a swarm of Agents with English Morphological agent, English Parser agent, Bilingual Translator agent, Sinhala Morphological agent, Sinhala Parser agent, Transliteration agent and a Manager Agent. The Ontology of the swarm of Agents comprises of four dictionaries and specific rules to implement the translation process. During a translation session, Agents negotiate through a common message space, a part of Manager Agent, and reach to a meaningful translation. Since the relevant Agents are created only when necessary, ABEES uses limited system resources and disregard the need for sequential processing. ABEES has been implemented using Java and SWI-Prolog to run on both Linux and Windows

Using a multi-agent system for supply chain management

Supply chain management (SCM) is a well-known example of a complex system. Classical computing technologies have shown little success in modeling complex systems. However, a large body of research in multi-agent system (MAS) technology has demonstrated how complex systems can be modeled to generate smart solutions, which could not be done otherwise. We have researched on the design and development of MAS for SCM. In this solution, each phase in the supply chain has been developed as an agent enabling communication, coordination and negotiation among the agents to achieve intended business goals. The study investigated decentralized collaborative planning architecture and agents are attached to different containers of the system. The containers have been implemented using a Java Agent Development Framework (JADE) and consist of diverse methods to support collaboration in the supply chain environment. Agents have different behaviors and their decisions are based on defined ontology. The identified key roles in the supply chain are raw material suppliers, manufacturers, distributors and retailers. They perform autonomous tasks with collaboration to accomplish final customer satisfaction

MASDM – A Multi agent solution for disaster management

In the context of large natural disasters like the Indian Ocean Tsunami in 2004 or Hurricane Katrina in New Orleans in 2005, the topic of disaster management has become a key concern both from a social and political point of view. Problem solving in an environment where a disaster has occurred is difficult and dynamic, requiring rapid decisions before, during and after the event. So a disaster management system should be capable of withstanding uncertainty, ambiguity and incompleteness given the dynamic and evolving nature of disasters. As a solution, a disaster management system based using agent technology has been implemented to provide proper management of resources and responsibilities for dealing with all aspects of a disastrous situation; in particular preparedness, response and recovery in order to lessen the impact of disasters. The system mainly consists of four agent swarms which are: forces swarm, aid store swarm, hospitals swarm and information providers swarm. Each swarm consists of number of agents whose tasks are explicitly defined. Agent interaction is the source of generating the intelligence. Agent communication, coordination and negotiation capabilities provide the ways and means of handling the complex nature of the domain

Existing systems and approaches for machine translation : a review

The Machine Translation has been a branch of Natural Language Processing, which comes under the broad area of Artificial Intelligence. Machine Translation system refers to computer software that translates text or voice from one natural language into another with or without human assistance. Worldwide, large number of machine translation systems have been developed using several approaches including human-assisted, rule-based, statistical, example-based, hybrid and agent based techniques. Among others, Statistical machine translation approach is by far the most widely studied machine translation method in the field of machine translation. The multi-agent approach is a modern approach to handle complexity of the systems in past five years. This paper reviews existing machine translation approaches and systems including existing chine translation systems

A Swarm of agents for language editing

Natural Language Editing has many complexities and ambiguities involved with the process. Natural Language editing in an automated environment is a complex task and due to this complexity, current automated tools face the limitation of perfectly editing a given write up considering both syntactic and semantic accuracy. Therefore, there is a need of evolutionary, adaptive, autonomous and dynamic approach for natural language editing. As the solution, ‘A Swarm of Agents for Language Editing’ is a multi agent based approach for evolutionary English editing. This system comprises a swarm of agents with spell checking agents, noun agents, verb agents, determiner agents, style agents and manager agent where each agent activates upon a request, executes and kills them at the end of the task. Unlike traditional editing software, this system is based on negotiations among different agents rather than instruction driven. In this system, English editing task involves interaction among different agents who take care of different aspects of a sentence structure such as noun, verb and determiners. These agents together with the manager agent negotiate with each others to generate an agreeable output. A common message space is used to enable the communication and thus negotiations among different agents in the swarm to come up with a commonly agreeable edited text

Multi agent based approach to assist the design process of 3D game environments

Designing complex and reasonable 3D environments for modern 3D games is one of the time consuming challenges faced by present video game industry. We have critically reviewed the existing approaches to automate the design of 3D environments. It was identified that current 3D environment generation techniques being specific to one or few types of environments and the lack of customizable frameworks which are common to many types of environments as the main issues to be addressed. According to literature, surprisingly complex and interesting global behaviours can arise in multi agent systems as a result of simple rules that are followed by number of simple gents operate in an environment. We hypothesize that this emergent behaviour of multi agent systems can be used to design 3D game environments with emergence properties that were not visible in initial constituents. The proposed solution provides a multi agent based approach to develop a framework which is common to design many types of 3D game environments. Each 3D model in a 3D game environment is associated with an agent with simple rules and this system allows users to introduce new 3D models and associate them with agent types. The main input for the proposed system is a parameterized description of an imaginary 3D environment. Output of the system is a 3D game environment with self organized 3D models positioned and oriented in most suitable places. The proposed approach has been evaluated by implementing a prototype and comparing the proposed approach with traditional 3D game environment design approaches

A Multi-agent system for web services in competitive marketing

This paper presents an approach for the creation and use of ontologies to support agent communication in competitive marketing process. Enterprise Application Integration remains a challenging field in IT, and this is particularly true for the online marketplace selections where a large number of independently operated information systems exist. The mission to integrate those systems (different super markets) to create a common marketplace becomes a complicated problem due to the vast number of different data models and structures that currently exists within these different domains. Existing technologies have given us some possible solutions but these typically lack extensibility. To overcome those limitations and provide better supermarket guidance, this approach proposes a solution with the utilization of an ontology based multi-agent system that runs on a competitive environment and proves to be highly efficient and a flexible supermarket guidance. The use of ontologies in message based communication gives meaning to the contents of the message sent between agents. This solution guides the supermarket customers towards more efficient shopping by pointing out the most appropriate supermarkets according to what they offer their facilities and other benefits providing provided without wasting customers’ time and money. W with the help of mobile and web service based technologies this also provides administration facilities to the supermarket owners for better service and revenue

Investigating the use of multi agent technology for agricultural information systems

The field of Agriculture could be considered as one of the main knowledge intensive domains. It is highly dependent on various aspects such as environmental conditions, market movements, pest controlling, crop management and soil conditions. These aspects are highly dynamic in nature, as a result, agriculture domain itself could be considered as a complex system. Throughout generations people were trying to simplify this complexity by addressing it through different means in different eras. As a result, various ICT approaches to address this complexity have been proposed. Subsequently, AI based approaches found to be the promising technology in the areas of this nature, because when it comes to real world problem solving, people survive within the complexity by being communicative with each other. This real life problem solving approach could be modeled as a Multi Agent System in which each inter connected entity could be modeled to represent a separate agent such as Environment Agent, Market Agent, Seed Agent, Soil Agent , Fertilizer Agent, and Pest Agent. In this research we hypothesise that, by modeling interrelated areas as agents and by means of negotiating among each entity, it is possible to solve queries related to agriculture domain. Users such as Agriculture researchers, “Govi Jana Seva” officers, and farmers could access the system through the Internet and mobile phones to place requests and queries. This paper present background information about this complex problem domain and evaluates the above hypothesis. At the same time it presents the technological and implementation details followed by the evaluation, conclusion and discussion

Mobile agent for monitoring computer networks

Network monitoring and maintenance have become crucial when a network comprises of several sub nets with heterogeneous hardware and software environments. This paper presents the designing and development of a Mobile Agent based as a solution for monitoring the campus wide local area network in the Sabaragamuwa University of Sri Lanka. The System comprises of three Agents; Host Agent - located in a host, Mobile Agent - movable on the network, and an Agent running on a Mobile phone. The Mobile Agent consists of a stationary unit and a mobile unit. The stationary unit deals with scheduling and controlling while the movable unit travels to locations with faults and does repairing. The mobile agent has also been provided with basic toolkits such as newly updated virus guard, commonly used software, patches, etc. The Agent running on the mobile phone is responsible for sending messages to the administrator to attend to some critical faults. The system has been developed on JADE. JADE-LEAP implements the Agent on the mobile phone with limited resources. The system has been tested on several sub nets to investigate the performance and accuracy in real cases