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... engines suffer from partial coverage of information. To solve this problem Etzioni (1996) suggested the use of Meta search engines to gather information from different search engines. Agents for E-commerce: agents are widely used in different applications in E-commerce such as: o Comparison Shopping Agents: agents are used to help users find the most suitable product while buying online.
It recommends product on other products and compare prices to find the best deal available. It also monitors new products and offers. This agent makes the process of online purchase more convenient and saves time, money on consumers. o Auction Bots: agents here are created to participate in online auctions for goods. According to Chavez and Maes (1996), there is a system called Kasbah where users create agents to sell or buy good according to their desires.
Agents track the sell and purchase that is going on and on a certain time they consider selling or buying. Agents for Human-Computer Interfaces: users work with program interfaces by deciding the action to be taken by clicking icons, buttons etc. the goal here is to build an interface that can work with the user to achieve a task together. The idea of agent interfaces is to change the function of interface from servant to the user into assistant that cooperates with the user. Also this helps the user in working with new interfaces easily before getting used to them.
Agents for Virtual Environments: agents here are used in film, entertainment and cinema industry. The key here is to provide real emotions to agents so that they won't appear as featureless characters. Agents are provided with the ability to understand human behaviour. By this, agents can act and react in a way that looks like real and more convincing to the audience. This is widely seen in different movies. Agents for Social Simulation: agents are used as experimental tools in social sciences.
The aim here is to use agents to represent individual people to simulate the behaviour of human societies. Different projects were done in the area of social simulation that aimed to use agents as human societies and see what kind of reaction will happen in different circumstances. This was used in measuring the effects of new policies on human societies. As an example a model of agents representing people was done to measure the reaction of putting the policy of asking people to consume less water in drought times. Agents for Industrial Systems Management: deployment of multi-agent systems in several industrial domains. In this case the system is enabled to plan the action it takes and communicate with other agents.
Agents here include both domain component which shows the domain functionality, and wrapper component which shows the agent functionality. Agents for Spacecraft Control: it provides real time advices to astronauts in the event of malfunction. It was very hard to use agent here since the system works in real time environment. Agents for Air-Traffic Control: agents are used to assist air-traffic controller in managing the flow of aircraft at an airport by monitoring previous estimates. 6. The Drawbacks and Limitations of Agent Solutions Wooldridge (2002) discussed a number of drawbacks that individuals and users might encounter while experiencing an agent-based system.
The basic three drawbacks are: Users have to tell every customization service what they want to know. This becomes a tedious job after a couple of time. Users need sometimes to fill a questionnaire or provide some personal information. This information will be used by the service provider to sell ads. This is a kind of personal information theft unless the user is aware that his information will be used. Users need to remember endless list of ID's for each service.
Since there is a big number of services, sometimes its easy to forget your ID easily On the other hand Jennings and Wooldridge (1998) stated that agent-based systems provided a number of solutions to different applications and domains. Nevertheless, those systems should not be overrated and used for any application. Using agent-based system will cause a number of problems if it was used regularly with no big need for it. The problems can be summarized as: No overall system controller: this means that agent-based systems must not be used in domains that have constraints to be maintained or in real-time applications. No global perspective: different decisions are taken by the local state of the agent.
This leads to incomplete global knowledge. Trust and delegation: agents work on behalf of users. So at the first a sense of trust should be build between users and agents and this might take a long period of time. During the building trust period, the agent must know its limitations and must not exceed its authority. The industry of agent system is facing the lack of standards for inter-agent communication language. Currently agents are limited by communication difficulties despite the development of a standard language called Knowledge Query and Manipulation Language (KQML), Seipp (2001).
The future now is to develop standard communication languages that enable efficient communication means between agents. 7. Agent Communication Languages (ACL) Agent communication languages provide the agents with the mean of interaction and knowledge exchange, the main two languages used for communication between agents are as following according to Alonso (2002): Knowledge Query and Manipulation Language (KQML): KQML can carry any representation language. It includes three layers: content, communication and message. The content layer stores the actual content in the programs own representation language. The communication layer encodes some features of the message such as sender and recipient ID and unique ID associated with the communication. The message layer encodes the message that one application would send to the other.
The basic design feature in KQML is to produce a language that is able to support different and multiple interesting agent architectures. One of the important things KQML introduced is an agent that performs a lot of communication services such as forwarding messages to named services. Foundation for Intelligent Physical Agents (FIPA) ACL: the FIPA specification consists of message type and description of attitude for the sender and receiver. It also includes protocols and the action requested. FIPA is similar to KQML in separating the outer language from inner language. The outer language is the meaning of the message, while the inner language describes beliefs and desires.
In conclusion, the two ACL's are the widely used communication languages, but till this moment there is a lack of universal agreement on semantics foundation, Hon (1999). 8. Current Research According to RMIT (2005), a lot of research is taking place now to improve and find new ways to develop software systems such as: The reason behind the lack of widespread agent technology is the lack of appropriate software engineering methodology. The research aims to support design processes in agent systems. Since the World Wide Web (WWW) includes loads of information. A range of agents are hosted by the web to serve users in information search. The research will be looking at the technical issues of adding new agents, and how the new agents can be located by other agents and work together with them.
Those two are a sample of a large number of research and projects done now days to improve agent technology and add new applications that can be supported by this technology. 9. Conclusion The emergence of the World Wide Web (WWW) provided people around the globe with the facility of information access; however the amount of information caused a lot of disturbance and difficulty while browsing. AI experts developed software called agents. Agents were used to help people to find the accurate information they look for. Since knowledge and improvement never stop, agents were developed to cover different application whether they are related to the web or not.
The different applications that agents are used in are: Agents for Business Process Management, Agents for Distributed Sensing, Agents for Information Retrieval and Management, Agents for E-commerce, Agents for Human-Computer Interfaces, Agents for Virtual Environments, Agents for Social Simulation, Agents for Industrial Systems Management, Agents for Spacecraft Control and Agents for Air-Traffic Control. The way agents operate depends basically on the environment they are located in. agents are provided with a knowledge base and interface engine. Learning agents include learning engine that enable them to learn from users or other agents Multi-agent systems are systems that include more than one agent, and those agents interact between each other to achieve a shared tasks or each agent can have a separate task. Different protocols arrange their interaction that is called as negotiations. Agents use Agent Communication Language (ACL) such as Knowledge Query Manipulation Language (KQML) or Foundation for Physical Intelligent Agents (FIPA).
Agent based systems can not be used in any application due to the difficulty of imposing the characteristics of agents on some applications that are limited by different constraints. Nowadays a lot of projects and research are taking place to improve and develop new features to agent systems to make the best and efficient use of this technology that is day by day spreading all over the world. Word Count 3, 503 References 1. Air (2000), Multi-Agent System: a Subtopic of Agent. [Online]. Available from: web [Accessed 8 th May 2005 ]. 2. Alonso, Eduardo. (2002), Agent communication slides, City University, London. [Online].
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