Software agents can be defined as semi-autonomous software entities which support individuals cope with the complexities when working in a distributed information environment. This paper describes how these intelligent agents involved in e-commerce transactions.
In recent years the World Wide Web has become largest market place due to its exponential growth enabled extensive progress in new information society functions such as electronic commerce. Electronic commerce, known as e-commerce, is a type of industry where buying and selling of product or service over electronic systems such as the Internet and other computer networks. Simply e-commerce is buying and selling over the internet medium. Electronic commerce involves business to business (B2B), business to customer (B2C) and customer to customer (C2C) transactions. It covers a wide variety of issues including security, trust, reputation, law, payment mechanisms, advertising, ontologies, electronic product catalogs, intermediaries, multimedia shopping experiences, and back office management. Agent technologies can be applied to any of these areas in e- commerce.
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2. Intelligent Agents
According to IDMs definition intelligent agents are software programs that carry out some set of tasks on behalf of a user or another program with some degree of independence. So doing, gain some knowledge or representation of the user’s desires. According to Meas definition software agents are computer programs that run in the background and perform tasks autonomously.
Software agents are becoming an important part of these Modern information systems because they diminish the complexity, and they achieve this technically and psychologically. Technically, each agent provides a locus of intelligence for managing a subset of the information in the system, either on its own initiative or under the direction of a user. Each intelligent agent can be readily replicated and then distributed as needed. This agent-based approach to information management is both scalable and cost-effective.
Psychologically, people need abstractions by which they can understand, manage, and use complex systems effectively. A natural and convenient abstraction appears to be one based on humanizing the information system components that is, treating the components as animate. In this abstraction, software components are like human agents. The abstraction is effective, because people have a lot of experience in dealing with other people, and they can apply their experience to understanding and dealing with complex software. 
Software agents were first used few years ago to filter information, match individuals with similar interests, and automate repetitive activities. More lately, agents have been applied to e-commerce, encouraging a revolution in the way people conduct transactions in e-commerce. Intelligent agents in e-commerce web sites can carry out many decision making and problem-solving tasks that usually require human intelligence, such as diagnosis, data sorting, planning, or negotiation. They can answer email messages, search the Internet for valuable information, carry out comparisons, or even become electronic pets.
O. Etzioni and D.S. Weld  defined a software agent as a software entity which functions continuously and independently in a specific environment often occupied by other agents and processes. The requirement for endurance and independence derives from human desire that an agent should be able to do activities in a flexible and intelligent manner reactive to changes in the environment without constant human observation. An agent that functions over a long period of time should be able to implement from its experience. Also, an agent should be able to occupy an environment with other agents and processes, and to be able to communicate and collaborate with them.
2.1 Types of Software Agents
Hendler  distinguishes four types of agents by function.
Problem-solving agents -They do many traditional planning expert systems did, namely collect data, analyze a situation, and make a conforming decision for how to act on the user’s behalf. Purchasing agents is an example for this category.
User-centric agents- These type of agents enable interaction with the user. Also they provide a better user interface by getting knowledge about the user’s system use preferences and tailoring the interface to the user preferences.
Control agents – They control the operation of some agents in a multi agent environment. In this context one needs to remember that agents are not only mobile, but also small in size, each with a very specialized capability. Hence, the interaction of several agents might be required to provide sufficient intelligence and capability. These are very progressive agents used in research experimentations.
Transaction agents- These agents translate information between different data standards within a unrelated database or file environment.
Between these four types, the ones that create contention are problem solving agents specializing in data gathering. They may be aided by transaction agents to access data from numerous data sources and may be controlled by control agents. However, the most important functionality is the ability to collect and analyze information from remote sites.
2.1.1 Characteristics of Software Agents
Dependable with the requirements of a specific problem, each intelligent agent might possess to a greater or lesser degree the attributes stating below [5, 6, and 7]
Reactivity: the capability of selectively sense and act.
Autonomy: goal-directedness, and self-starting behavior.
Collaborative behavior: can work in collaboration with other agent to attain a mutual goal.
“Knowledge-level” communication ability: their ability to communicate with human and other agents with language more approaching human-like speech than symbol-level protocols.
Inferential capability: can perform on abstract task specification using previous knowledge of general goals and chosen methods to achieve flexibility.
Temporal continuity: persistence of uniqueness and state over long time periods.
Personality: the ability of exhibiting the attributes of a believable character such as emotion.
Adaptively: being able to learn and progress with experience.
Mobility: ability to transfer in a self-directed way from one host platform to another.
3. Intelligent Agents in e-Commerce
Artificial intelligence (AI) started to play a important role in many leading information systems. In the past, its use of AI has been limited due to its complexity, huge designs and lack of expertise in system developers. AI involvement is now essential in nondeterministic systems such as workflow, data mining, production planning, supply chain logistics, and most lately, e-commerce.
Intelligent agent technology is the next logical step in overcoming some shortcomings in e-commerce. Namely, successful computer systems underlying e-commerce require judgment and the knowledge of experts such as buyers, contract negotiators and marketing specialists 
Also e-commerce covers a broad range of issues; some of them are away from the scope of consumer buying behavior model. There are a variation of theories and models that describes buying behavior, such as the Nicosia model, the Howard- Sheth model, the Engel-Blackwell model, the Bettman information-processing model, and the Andreasen model .Acoording to Aleksander Pivk and MatjaÅ¾ Gams these models all have a comparable list of six fundamental stages of the buying process, which also relevent where agent technologies apply to the shopping experience
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Identification: In that stage characterizes the buyer becoming aware of particular unmet need by inspiring through product information. Agents can play an significant role for those purchases that are repetitive (supplies) or predictable (habits). One of the oldest and simplest There are many examples in abundant use, one very aware of is a “notification agent” called “Eyes” by Amazon.com, which observers the catalog of books for sale and notifies the customer when certain events occur that may be of interest to the customer
Brokering: There are two types of brokering namely product brokering and merchant brokering. In product brokering once a buyer has recognized a requirement to make a purchase the buyer has to determine what to buy through a critical evaluation of retrieved product information. There are several agents systems that lower consumers search cost when deciding which products best meets their needs. The result of this stage is a get attention to set of goods. In merchant brokering stage combines the consideration set from the previous stage with merchant-specific alternatives to help determine who to buy from.
Negotiation: in this stage of buying behavior, price and other terms of the transaction are settled between merchants and buyers. Real-world scenarios negotiation increases transaction costs that may be too high for either consumers or merchants.. The most of business-to-business(B2B) transactions contain negotiation.
Payment and Delivery: this stage can either indicate the end of the negotiation stage or cause to place another order. In some cases, the presented payment or delivery options can affect product and merchant brokering.
€ Product Service and Evaluation: this post- purchase stage contains of product service, customer service, and an € evaluation of the satisfaction of the€ € total buying experience and decision.
Considering above five stages, It can be recognized the roles of agents as mediators in e-commerce. The nature of agents makes them suitable for mediating those consumer behaviors involving information filtering and retrieval, personalized evaluations, complex coordination, and time-based interactions. Those roles correspond most especially to the need identification, product and merchant brokering, and negotiation stages of the buying behavior model.
4. Benefits of intelligent agents in e commerce
5. Limitations of Intelligent Agents
A major limitation intelligent agent technology using most e-commerce activities is that agents can pose a security risk to remote hosts as well as their original host). A broad discussion of these risks and possible countermeasures is provided to International Journal of Electronic Commerce by T. Mandry ,G.Pernul and A. Röhm the following possible risks were identified.
Stealing data and Illegal access – Web agents may try to get access to databases they are not permitted to access or for which there is an access charge.
Free use of resources – Agents always tries to “steal” resources from remote hosts. As long as this is in line with accepted protocols, it is an acceptable practice. However, if agents cover-up as alternate processes, they may use insupportable levels of resource.
Unauthorized program execution – This also known as Trojan horse. Agents can be masquerade and then execute programs that are eventually harmful to the remote hosts. Such Trojan horses attacks have now been used frequently on the Internet..
Data stripping or alteration (by server). Technically it is possible to strip Web agents of their data. This is mostly a concern for a site that sends out agents to remote hosts, but also it could potentially affect other sites. For instance, suppose Buyer has a trusted relationship with both Seller 1 and Seller 2. However, there exists a competitive relationship between the two sellers. An intelligent agent that originates from Buyer and travels to Seller 1 and then to Seller 2 could be stripped by Seller 2 to obtain competitive data about Seller 1.
Resource exhaustion resulting in denial-of service -. Web agents can exhaust remote host properties to the point where the remote host can no longer function correctly.
Deceitful agent behavior. – Agents can mislead other agents or hosts about their intent and can lie about transactions.
This paper describes how intelligent software agent can automate and add value to e-commerce transactions and negotiations. By using intelligent agent based e-commerce techniques, businesses can more effectively and efficiently make decisions since they have more accurate and reliable information and recognize consumers’ perceptions and behaviors. Benefits and limitations of using intelligent agents in e-commerce are also discussed through this paper.
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