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Chapter 11 Managing Knowledge 473

Electric engineers used genetic algorithms to help optimize the design for jet
turbine aircraft engines, where each design change required changes in up to
100 variables. The supply chain management software from i2 Technologies
uses genetic algorithms to optimize production-scheduling models incorpo-
rating hundreds of thousands of details about customer orders, material and
resource availability, manufacturing and distribution capability, and delivery
dates.

INTELLIGENT AGENTS

Intelligent agent technology helps businesses navigate through large amounts of
data to locate and act on information that is considered important. Intelligent
agents are software programs that work without direct human intervention
to carry out specific tasks for an individual user, business process, or software
application. The agent uses a built-in or learned knowledge base to accom-
plish tasks or make decisions on the user’s behalf, such as deleting junk e-mail,
scheduling appointments, or traveling over interconnected networks to find the
cheapest airfare to California.
There are many intelligent agent applications today in operating systems,
application software, e-mail systems, mobile computing software, and network
tools. For example, the wizards found in Microsoft Office software tools have
built-in capabilities to show users how to accomplish various tasks, such as
formatting documents or creating graphs, and to anticipate when users need
assistance. Chapter 10 describes how intelligent agent shopping bots can help
consumers find products they want and assist them in comparing prices and
other features.
Although some intelligent agents are programmed to follow a simple set
of rules, others are capable of learning from experience and adjusting their
behavior. Siri, an application on Apple’s iOS operating system for the iPhone
and iPad, is an example. Siri is an intelligent personal assistant that uses voice
recognition technology to answer questions, make recommendations, and
perform actions. The software adapts to the user's individual preferences over
time and personalizes results, performing tasks such as finding nearby restau-
rants, purchasing movie tickets, getting directions, scheduling appointments,
and sending messages. Siri understands natural speech, and it asks the user
questions if it needs more information to complete a task. Siri does not pro-
cess speech input locally on the users’s device. Instead, it sends commands
through a remote server, so users have to be connected to Wi-Fi or a 3G signal.
Many complex phenomena can be modeled as systems of autonomous agents
that follow relatively simple rules for interaction. Agent-based modeling
applications have been developed to model the behavior of consumers, stock
markets, and supply chains and to predict the spread of epidemics.
Procter & Gamble (P&G) used agent-based modeling to improve coordination
among different members of its supply chain in response to changing business
conditions (see Figure 11.11). It modeled a complex supply chain as a group of
semiautonomous “agents” representing individual supply chain components,
such as trucks, production facilities, distributors, and retail stores. The behavior
of each agent is programmed to follow rules that mimic actual behavior, such as
“order an item when it is out of stock.” Simulations using the agents enable the
company to perform what-if analyses on inventory levels, in-store stockouts,
and transportation costs.

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