An intelligent agent can change your business. And no, we are not talking about espionage and subterfuge but about tech entities. Read on…
a number of enterprises these days employ abstract intelligent agents (AIAs). These are ‘intelligent’ entities that can scrutinise the given milieu and respond to variations in specific parameters. As AIAs have the knack to learn from their surroundings and are also specially ‘trained’ to use their knowledge, a number of companies are using them for meticulous precision and accuracy in calculations.
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AIAAgents with intelligence
An intelligent agent has the ability to observe its surroundings and react according to the changes. But it is not fully self-reliant. In most cases, the implementer is required to closely monitor the working of these agents.
In actual practice we deploy many types of multi-agent systems (MASs) for better accuracy in tasks like online trading, disaster response and so on. Online trading is too difficult for an individual agent (or monolithic system) to handle. If you are in this domain, you can incorporate such a system in a business framework, provided you have the technical expertise.
The agents in a multi-agent system could be robots or human beings. And their environment may have other agents, objects, and global and local variables. Based on the behavioural capabilities of the agents, you may classify them as reactive agents (whose prediction factor depends only on the environment) and proactive agents that work in a framework where the environment and its own state are considered. Some agents are non-adaptive while some others are adaptive. One has to be very vigilant while choosing the agent for a particular business.
Technically speaking, MAS agents can communicate using a weighted request matrix and a weighted response matrix. The specification style adopted by the developers is elegant and comprehensible. Even if you are a novice in this realm, you can imbibe the agent’s ‘functions, rules, knowledge and strategies’ by looking at it. And there are even many other schemes for MASs-viz, the challenge-response-contract-that are extremely practical and commanding.
Since they are able to solve problems by themselves, these are aptly called as self-organised systems. The success of MAS has triggered advanced level research in agent-oriented software engineering; organisation; beliefs, desires, and intentions (BDI); distributed problem solving and multi-agent learning. By suitably using communication and negotiation capabilities, agents help enterprises in promoting their products and solutions.
Agents in action
When you purchase books from Amazon.com, have you ever wondered how the site is able to display a list of books that you may like? Buyer agents (shopping bots) are behind them. The bot analyses what you are buying now and what you have bought in the past. Then, it uses its ‘knowledge base’ to furnish suggestions. These agents can be customised to get information about goods and services. You must have used ‘user’ agents (personal agents), too-when your system plays games as your opponent, it is doing the function of an agent.
If you look at the website of NASA’s (National Aeronautics and Space Administration’s) Jet Propulsion Laboratory you can find information about monitoring-and-surveillance (predictive) agents. Though these agents as such can’t be employed in a business framework, they can be tailored to perform specific tasks like monitoring your competitors’ prices.
Data mining agents are also widely being used in the industry. And one may often have a data warehouse that contains information from many other sources. Agents can come out with ways to boost sales or keep customers loyal by using data mining techniques coupled with other AI solutions.
The list of applications does not end here. There is a lot more that you can do with such agents. You can even simulate the movement of a large number of objects or characters using them. Some R&D teams opt for fuzzy agents and distributed agents to perform definite missions.
Why are agents unique?
Their ability to learn and adapt makes agents exceptional. Not surprisingly, many industries are investing in their development. Many companies have R&D teams working on agents. Though you can build an agent from scratch, there are some frameworks that implement common standards, such as JADE.
JADE is essentially a middleware (a type of connector) that can be used for the development of applications. It can administer both mobile and fixed environments. A peer-to-peer intelligent agent approach is employed here. You can use JADE for developing simple reflex agents, model-based reflex agents, goal-based agents, utility-based agents and learning agents, provided your company’s CTO is good in customising complex frameworks. Once you employ an agent-where it is an agent for decisions, inputs, learning, processing, world/global agent, or a spatial or temporal agent*-you will see the impact right away in your turnover. That’s the clout of artificial intelligence (AI)!