Intelligent agent
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In computer science, an intelligent agent (IA) is a software agent that exhibits some form of artificial intelligence that assists the user and will act on their behalf, in performing repetitive computer-related tasks. While the working of software agents used for operator assistance or data mining (sometimes referred to as bots) is often based on fixed pre-programmed rules, "intelligent" here implies the ability to adapt and learn.
An agent is an entity which percepts through sensors and acts through actuators. An agent program can be defined mathematically as an agent function which maps every possible percepts sequence to a possible action the agent can perform:
f:P * − > A
The program agent, instead, maps every possible percept to an action.
It is possible to group agents into four subsets:
- simple reflex agents;
- model-based reflex agents;
- goal-based agents;
- utility-based agents.
1. Simple reflex agents
Simple reflex agents acts only on the basis of the current percept. The agent function is based on the condition-action rule:
if condition then action rule
This agent function only suceeds when the environment is fully observable.
2. Model-based reflex agents
Model-based agents can handle partially observable environments. Its current state is stored inside the agent maintaining some kind of structure which describes the part of the world which cannot be seen. This behaviour requires informations on how the world behaves and works. This additional information is called model.
3. Goal-based agents
Goal-based agents are model-based agents which store informations regarding situations that are desirable. This allows the agent a way to choose among multiple possibilities, selecting the one which reaches a goal state.
4. Utility-based agents
Goal-based agents only distinguish between goal states and non-goal states. It is possible to define a measure of how much desirable is a particular state. This measure can be obtained through the use of the so called utility function which maps a state to a measure of the utility of the state.
In some literature IAs are also referred to as autonomous intelligent agents, which means they act independently, and will learn and adapt to changing circumstances. According to Nikola Kasabov IA systems should exhibit the following characteristics:
- learn and improve through interaction with the environment (embodiment)
- adapt online and in real time
- learn quickly from large amounts of data
- accommodate new problem solving rules incrementally
- have memory based exemplar storage and retrieval capacities
- have parameters to represent short and long term memory, age, forgetting, etc.
- be able to analyze itself in terms of behavior, error and success.
According to the Third Canadian Edition of "Management Information Systems for the Information Age" there are four essential types of Intelligent Agents:
- Buyer agents or shopping bots
- User or personal agents
- Monitoring-and-surveillance agents
- Data Mining agents
1. Buyer Agent
Buyer agents travel around a network (i.e. the internet) retrieving information about goods and services. These agents, also known as 'shopping bots', work very efficiently for commodity products such as CDs, books, electronic components, and other one-size-fits-all products. Amazon.com is a good example of a shopping bot. The website will offer you a list of books that you might like to buy on the basis of what you're buying now and what you have bought in the past.
2. User or Personal Agents
User agents, or personal agents, are intelligent agents that take action on your behalf. In this category belong those intelligent agents that already perform, or will shortly perform, the following tasks:
- Check your e-mail, sort it according to priority (your priority), and alert you when good stuff comes through - like college acceptance letters
- Play computer games as your opponent or patrol game areas for you
- Assemble customized news reports for you. There are several versions of these, CNN being a prime example
- Find information for you on the subject of your choice
- Fill out forms on the Web automatically for you, storing your information for future reference
- Scan Web pages looking for and highlighting text that constitutes the "important" part of the information there
- "Discuss" topics with you ranging from your deepest fears to sports
3. Monitoring-And-Surveillance Agents
These agents, also known as "predictive agents", are intelligent agents that observe and report on equipment. For example, NASA's Jet Propulsion Laboratory has an agent that monitors inventory, planning, and scheduling equipment ordering to keep costs down, as well as food storage facilities. These agents usually monitor complex computer networks that can keep track of the configuration of each computer connected to the network.
4. Data Mining Agents
A data mining agent operates in a data warehouse discovering information. A 'data warehouse' brings together information from lots of different sources. 'Data mining' is the process of looking through the data warehouse to find information that you can use to take action, such as ways to increase sales or keep customers who are considering defecting. 'Classification' is one of the most common types of data mining, which finds patterns in information and categorizes them into different classes. Data mining agents can also detect major shifts in trends or a key indicator and can detect the presence of new information and alert you to it.
There are hundreds of intelligent agents, or 'bots', for a wide variety of tasks. The BotSpot website at [5] is a good places to look for the different types of agents available.
[edit] See also
- Agent
- Intelligence
- Cognitive agent
- Agent environment - discussion of environment types
- Fuzzy agents - IA implemented with adaptive fuzzy logic
- Cognitive architectures - IA considered to be self-aware
- Multi-agent system and Multiple agent system - multiple interactive agents
- Reinforcement learning
- Cybernetics, Computer science
- Semantic web - making (approximations of) the meaning of web pages available for automated processing
- Federated search - the ability for agents to search heterogeneous data sources using a single vocabulary
- Cognitive radio - a practical field for implementation
[edit] References
- ↑ rsnz.org Characteristics of an intelligent agent
- ↑ 3, 4, 5 Haag, Stephen. "Management Information Systems for the Information Age", 2006. Pages 224-228
