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MANAGING THE DIGITAL ENTERPRISEMICHAEL RAPPA

<7>DIGITAL AUTOMATA

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Hungry minds:

Know your Enemy:
Tracking Botnets

Honeynet Project

Agents and Other
'Intelligent Software'

Maria Gini

Intelligent Agents
Stuart Russell
Peter Norvig

Software Agents
Hyacinth Nwana

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Case study:

RealDialog

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Places to visit:

CMU Software
Agent Lab

GroupLens

IBM Autonomic
Computing

UMBC AgentWeb

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Previous topic:

Digital Markets

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Intelligent Agents
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The promise (and peril) of a world composed of bits is that it opens the door to automation; to let computers alone do what we cannot or prefer not to do ourselves. Computer automation takes many shapes. It can be as basic as a program that spares us from the tediousness of deleting spam from our email, or as evolved as one that simulates human interaction to answer customer service questions.

Software programs that operate independently with little or no human intervention are varied in form and function and go by several names — agents, bots, recommender systems, collaborative filtering, avatars, chatterbots, and more — but all could be "The first phase of the Web is human communication..." Tim Berners-Leecharacterized generally as digital automata [au•tom•ata], to use the Latin word for self-operating machines. As remarkable as progress has been with digital automata, there is much more to be done. Now that computers communicate with each other across the Internet, opportunities to automate tasks abound. But to realize the full potential of automata on the Web, there is a need for further work to make information understandable to machines. This is the goal of the Semantic Web, an ambitious project to create machine-readable protocols that convey meaning about data (metadata and ontologies) that will allow computers to act upon data independently to perform tasks on our behalf.

Another front in the advancement of computer automation is autonomic computing. Here the goal is to develop a computer that is capable of managing itself to a significant degree without human intervention. Researchers envision a machine that could configure itself, discover and correct faults, monitor and optimize how it functions, identify threats and protect itself from attack among other things.

Not all automation is helpful. A troublesome trend in security is the proliferation of automated attack tools that can be used to cause widespread harm to computer networks. Distributed denial of service (DDos) attacks use automated techniques, like worms, to compromise and seize control of thousands of computers, called a Botnet, and then use them to shutdown targeted Web sites. There are spambots that troll the Internet to harvest email addresses from Web pages. Indeed spam itself is made possible largely through the use automated tools that send out millions of messages each day. Sometimes those messages carry viruses and worms, which replicate themselves and very quickly infect millions of computers across a network. What is worse, automated attack tools can be simple to use with devastating effect in the hands of novices.

FUNCTIONS PERFORMED BY DIGITAL AUTOMATA
Collect Programs that gather and store information in databases, such as search engine crawlers. [Googlebot]
Filter Programs that sort and classify information based on a given set of criteria. [SpamAssassin]
Recommend Programs that analyze information such as preferences to make recommendations. [MovieLens]
Monitor Programs that scan information to detect changes and respond, for example, by issuing an alert. [Copernic]
Find Programs that autonomously conduct searches based on a set of given criteria.
Process Programs that perform regularly scheduled processes, such as with basic computer maintenance. [Macaroni]
Transact Programs that perform automated transactions, such as with auction bidding. [Auction Sentry]
Simulate

Programs that simulate human activity such as speech, facial expressions, or motion. The representations may be realistic or stylized. [CyberBuddy, Lauren]

Learn

Programs that adapt to new information such that learning may occur. [Creature Labs]

Negotiate Programs that negotiate with other programs in a multi-agent system.
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Hear the podcast:

Podcast by Professor Michael Rappa

Audio | Transcript

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Things to read:

Learning Objectives

__/ 01-06-2003 \__
The Vision of
Autonomic Computing

Jeffrey Kephart
David Chess

__/ 08-02-2001 \__
Patterns for e-Commerce
Agent Architectures

Michael Weiss

__/ 07-18-2000 \__
Electronic Commerce Recommender
Applications

J. Ben Schafer, et al.

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On the airwaves:

__/ 11-01-2007 \__
Collective Wisdom: 'We
Are Smarter Than Me
'
Barry Libert
Jon Spector

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Next topic:

Auctions

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© 2009 Michael Rappa

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