PERSPECTIVES ON USAGE OF AGENTS IN PERSONAL

KNOWLEDGE MANAGEMENT

Kaspars Osis and Janis Grundspenkis

Institute of Applied Computer Systems, Riga Technical University, Meza 1/4, Riga LV 1048, Latvia

Keywords: Intelligent agents, Personal knowledge management, Knowledge worker.

Abstract: It is frequently mentioned that nowadays is the information age. Knowledge becomes the most important

asset for individuals and organizations. And more increasingly knowledge has been viewed as an active area

of research. Accordingly there is a need for highly qualified knowledge workers. That in turn implies a

necessity for on an effective technology based education system, which provides a foundation for obtaining

well educated specialists. Thus perspectives of personal knowledge management (PKM) environment are

explored in this context. This environment is not just focused on an individual. Rather it is involving also

collaboration for knowledge exchange thus forming communities of practice. The central concept of the

paper is knowledge worker surrounded by several layers of agents such as personal agents, communication

agents and so called “engine room” agents like database and network agents. The next step related to

different types of agents would be to consider that all or part of them could be mobile agents. Possible

future opportunities for PKM are explored in this respect and potential benefiting parties are identified.

1 INTRODUCTION

In couple last decades one can observe a historic

transition from the industrial age to the information

age. Some may even argue that we already are in the

information age. Creation and consumption of

material goods, usage of fixed procedures and

following standardized information routines can be

named as characteristic elements of industrial age. In

opposite to latter mentioned, the information age can

be described as creating and consuming information,

using ad-hoc approaches and non-standardized

information for decision making and reaching

solutions. The Web and the Internet have shifted

even more focus towards the importance of

information. That changes the way information is

stored, presented, consumed and shared with others.

That in turn provides new options for doing business

in different areas - be it accounting, car engineering,

or teaching. The development of the Web has been

very rapid. So has been with the growth of

information amounts people and software systems

have to deal with. That is known as information

overload. In addition workspace equipment is

becoming more sophisticated which requires

additional skills and knowledge to handle it. As a

result work is becoming increasingly complex

(Wiig, 2004) and more complicated processing

systems have to be developed to make sense out of

these vast amounts of information. That has led to

recognition that knowledge has become the most

important asset for organizations and for individuals,

which more increasingly has been viewed as an

active area of research. This shift from information

to knowledge has been a reason for appearance of so

called “knowledge work”, which might be seen as a

new position within a list of intellectual jobs.

Increased importance and usage of knowledge in

business and in everyday life creates a necessity for

well educated people. That implies a need for on an

effective technology based knowledge management

and education system, which would pave the road

for a new knowledge-based society and economy,

and would allow ambient participation in a social

and economic life. This paper reports on one stage

of broader research targeted at perspectives of using

agents in the environment of personal knowledge

management. At this stage of research a personal-

knowledge based worker environment supported by

number of agents is defined. And next it is viewed in

perspective of PKM and possible future

opportunities.

332

Osis K. and Grundspenkis J. (2009).

PERSPECTIVES ON USAGE OF AGENTS IN PERSONAL KNOWLEDGE MANAGEMENT.

In Proceedings of the International Conference on Knowledge Management and Information Sharing, pages 332-337

DOI: 10.5220/0002331303320337

 SciTePress

2 TOWARD AGENTS

One could assume that over twenty years it is more

than enough to get straight with the definition of the

basic concepts. This is not the case regarding agents.

The concept ‘agent’ has not been defined in a single

unified way which could be widely accepted. Thus

there are several approaches how to define an agent.

The term “agent” itself surfaced for the first time in

mid-1950s with John McCarthy (Bradshaw, 1997).

The American Heritage Dictionary defines an agent

as “one that acts or has the power or authority to act;

or one empowered to act for or represent another; or

a means by which something is done or caused;

instrument” (Pickett, 2000). General software agent

definition says that an agent is every program that

acts in the name of its user (i.e. human) (Bradshaw,

1997). A more specific definition of a software agent

which could be more widely acceptable is given by

Shoham: a software entity which functions

continuously and autonomously in a particular

environment, often inhabited by other agents and

processes (Bradshaw, 1997). Also Wooldridge and

Jennings point out that first of all an agent is a

computer system situated in some environment, and

that it is capable of autonomous action in this

environment in order to meet its design objectives

(Wooldridge and Jennings, 1995). Agents’

autonomy is perceived as equivalent ability to

humans’ free will (Vidal and Buhler, et. al. 2001).

Agents may or may not have several

characteristics or features. They are: autonomy,

social ability, reactivity, pro-activity, mobility,

veracity, benevolence, rationality (Wooldridge and

Jennings, 1995; Padgham and Winikoff, et. al.

2008). In addition to already mentioned agent

features Bradshaw adds: temporal continuity,

personality, adaptivity (Bradshaw, 1997).

Agents can be divided in types. Nwana comes up

with several of them. He classifies agents as

collaborative agents, interface agents, mobile agents,

information agents, reactive agents, hybrid agents,

heterogeneous agent systems, and smart or

intelligent agents (Nwana 1996).

2.1 Intelligent Agents

A bit more about intelligent agents - what are they?

Wooldridge defines intelligent agents as ones that

are forced to work sturdy in rapidly changing,

unpredictable, and open environments, where exists

a good possibility that actions may fail (Wooldridge,

1999). He adds that an agent is a computer system

capable of flexible autonomous action in order to

meet its design objectives. By flexible he means that

such system must be responsive, proactive and

social. Australian software company JACK

uses

intelligent agents in their commercial applications.

There an intelligent agent is being seen as an

encapsulated computer system that works within

larger systems, or in other environments, and one

that can reason. It can perform functions that require

higher-level cognitive abilities (AOS Group, 2009).

2.2 Mobile Agents

In turn a mobile agent is an execution unit able to

migrate in an autonomic way to another host,

transporting along with itself its code and state; and

seamlessly resume its execution in this new

environment before that installing its own code.

(Nwana, 1996; Lange and Oshima, 1999). The term

“state” usually means agent parameters’ values,

which helps agents to realize from which place to

continue to execute interrupted work; “code” in

other hand in a sense of object oriented context

means class code, used by agent to execute itself

(Lange and Oshima, 1999).

3 PERSONAL KNOWLEDGE

MANAGEMENT

The term ‘personal knowledge management’

consists of three words – personal, knowledge and

management. Obviously personal refers to an

individual and to everyday tasks he or she performs

or is intending to do. What is knowledge? If to look

in a personal – human perspective, then knowledge

and its physical location is mainly in the brain and

thus it appears as our memories and skills

(Apshvalka, 2004). However she also points out that

knowledge is rather intangible and that it can not be

fully realizable in common with all our human

being. Thus considerable role is played by

individual’s characteristics such as volition,

psychological traits, motivation and his or her

intelligence. A broader definition is nailed down by

Thomas Davenport, where knowledge is “a fluid

mix of framed experience, values, contextual

information, and expert insight that provides a

framework for evaluating and incorporating new

experiences and information. It originates and is

applied in the minds of knowers. In organizations it

often becomes embedded not only in documents or

repositories but also in organizational routines,

processes, practices, and norms” (Davenport and

PERSPECTIVES ON USAGE OF AGENTS IN PERSONAL KNOWLEDGE MANAGEMENT

333

Prusak, 2000). Knowledge management (KM) in its

classic way is viewed in business context in

organization. Thus KM is defined as such which

enables creation, sharing and utilization of

knowledge in order to achieve business goals

(Quintas 1999). The primary goal of KM in this

context is identified as “to facilitate opportunistic

application of fragmented knowledge through

integration” (Tiwana 2002).

PKM is rather overlooked area within KM even

though lately it picks up speed again. “Definitions of

PKM revolve around a set of core issues: managing

and supporting personal knowledge and information

so that it is accessible, meaningful and valuable to

the individual; maintaining networks, contacts and

communities; making life easier and more

enjoyable; and exploiting personal capital”

(Higgison 2004). Eric Tsui defines PKM as “a

collection of processes that an individual needs to

carry out in order to gather, classify, store, search

and retrieve knowledge in his/her daily activities”.

He adds that “activities are not confined to

business/work-related tasks but also include personal

interests, hobbies, home, family and leisure

activities” (Tsui 2002). More laconic is Steve Barth

as he says that PKM is taking responsibility for what

you know, who you know, and what they know

(Barth 2000). Within essence of this short definition

lays the cultural and collaborative aspect of PKM.

Meaning that PKM is not focused just on an

individual, but it is more concentrating on culture

and collaboration between knowledge workers. Thus

PKM is fostering a creation of communities of

practice (CoPs) which serve as a fertile ground for

knowledge sharing and subsequently for knowledge

creation. There are already a number of different

types of CoPs established online starting from

professional, business, everyday practical questions

related ones and ending with social network type of

CoPs. Users’ comments next to bidder’s history on

eBay auction site or customers’ descriptions of

bought goods on Epinions.com are examples of

CoPs related to everyday practical questions. Instead

LinkedIn is both an example of a professional CoP

and a social network CoP.

3.1 Knowledge Worker

Thus PKM is also geared toward CoPs, culture and

collaboration of knowledge workers. That requests

for a closer look at these individuals. Who are they?

For the first time the term “knowledge worker”

appears in a book by Peter Drucker (Drucker 1959)

in the middle of previous century. Since then this

term has been looked at several times. Really in the

spot light it started to appear at the end of previous

century. A well known author on knowledge and

knowledge management Thomas Davenport defines

knowledge workers as ones that have high degrees

of expertise, education, or experience, and the

primary purpose for their jobs involves the creation,

distribution, or application of knowledge (Davenport

2005). In short, intellectual job they do is the way of

working they do for living. Davenport goes even

further – he names categories or areas where

knowledge workers would be most probably located.

These are: management; business and financial

operations; computers and mathematics; architecture

and engineering; life, physical and social scientists;

legal area; healthcare practitioners; community and

social services; education, training and library; and

arts, design, entertainment, sports, media (Davenport

2005). He adds, that this forms a respectable almost

one third of all the labor force in United States. No

doubts that similar situation might be observed in

other countries as well.

If to bring focus back on the individual himself

or herself, then ideally, knowledge workers should

possess not just technical know-how, but also sure

sense of the cultural, political, and personal aspects

of knowledge (Davenport 2000). That means that

personality characteristics of knowledge workers

most probably play an important role in how he or

she is at finding, understanding, and making use of

organizational knowledge (Dalkir 2005). This is true

not just in case of organizational knowledge. It is

true also in managing and enhancing knowledge

worker’s own knowledge as well. John Brown says

that innovation takes place at all levels of the

company – not just in the research department

(Drucker and Garvin, et. al. 1998). This can be

derived even further by saying that innovation and

new ideas in knowledge worker’s level happen at all

places and times within his or her daily routine – not

just at work or school. Thus it is important that

knowledge worker has at hand a PKM system

(PKMS). It is a complex system and includes

psychological, social and technological aspects

(Apshvalka and Grundspenkis, 2005). The

performance of PKMS is conditioned with

knowledge workers emotions, perceptions, believes,

objectives, surrounding society and environment.

Also technologies play an important role. Such

system can serve as a support for performing simple

information management tasks as well as a support

for much more intellectual activities, for example,

such as collaborative learning of a new language

while commuting by train.

KMIS 2009 - International Conference on Knowledge Management and Information Sharing

334

Figure 1: Knowledge worker’s agent environment.

4 AGENT BASED PKM SYSTEM

If to look in more details one can easily see that an

individual might be involved in a number of very

different activities that requires knowledge and

skills. He or she might be studying at university a

new subject, looking for a new or better job, setting

up a meeting with peers to get help on chemistry

homework, booking a plain ticket for attending an

international conference and so on. Many times in

these activities a searching is involved for

information, communication, scheduling or

messaging just to mention a few of them. In PKMS

all these activities require an intelligent support,

which may be implemented in the form of

communities of intelligent agents. There can be

distinguished three groups of agents (see Figure 1)

that could form a basis for knowledge worker’s

agent environment.

First, agents that can serve as the hard work

performers – a driving force for so called “engine-

room”, which basically is an integrated set of

hardware, software and technologies to assure

knowledge acquisition, processing, storage and

representation as it is stated for organizations in

(Grundspenkis, 2003). Here we try to use this

concept for PKM. Secondly, they are agents that

enable communications. And finally, these are

personal agents that are most closely tied with

knowledge workers.

The idea behind “engine room” agents is that

nowadays there are plenty things to-do related with

rather technical tasks that knowledge worker has to

embrace in order to streamline his or her daily

activities. Such agents, for example, could provide a

helpful hand in monitoring and collecting

information from data streams. They could

appropriately react on changes in combined “engine

PERSPECTIVES ON USAGE OF AGENTS IN PERSONAL KNOWLEDGE MANAGEMENT

335

room” environment, which could consist from LAN,

WAN, the Internet, hardware used by knowledge

worker, etc. Such environment for most people is

increasingly difficult and time consuming to handle.

As “engine room” agents can be mentioned database

agents – for storing knowledge elements and

information, hardware agents – for performing

system adjustments to particular user’s hardware,

physical network agents – for supporting PKMS on

a network level, connection agents – for establishing

connections and determining appropriate protocols,

local content agents – for taking care of different

knowledge elements stored on user’s device,

intelligent Web agents – for performing advanced

knowledge elements’ acquiring and processing

activities on the Web, and social network agents –

for supporting low level activities in relation with

social networks. Also there can be mentioned other

agents that provide means to support technologies

for fundamental functions of knowledge work, for

example, software distribution agents, which main

goal is to take care of timely software updates and

software installation package deliveries.

Other group of intelligent agents is

communication agents. As their name says by itself,

these agents are in charge of communications. For

individual situated in multi-agent environment

communications is very important point of focus in

order to have effective knowledge creation,

acquisition, sharing and distribution in the PKMS.

These agents include messaging agents (Knapik and

Johnson, 1998), cooperative agents that are geared

towards communication with other agents and

collaborative agents that focus on performing tasks

in collaboration with other agents. Thus these agents

support the collaboration, communication and

culture characteristics of PKM. Also team agents

(Ellis and Wainer, 2002) that support groupware

technologies can be mentioned as part of

communication agents.

Personal agents are ones that are directly

influenced by the individual, support interaction

with particular hardware device, and provide help in

knowledge work. These agents include assistant

agents, search agents, filtering agents and workflow

agents (Knapik and Johnson, 1998). Assistant agents

can provide help with automated hotel or flight

booking, scheduling meetings by taking into account

available time frames and locations, or they could

handle individual’s e-mail system by sorting

incoming e-mails and reminding to reply. Search

agents are most well know and widely used ones, for

example, one can think about Paper-clip agent in MS

Office. Such agents can be geared towards different

type of searches like keywords in scientific articles

or database indexes, or yellow page directories on

corporate network. Filtering agents can be used for

monitoring information on the Web or for suspicious

pattern recognition in home video surveillance

system. Workflow agents can be helpful in

scheduling daily tasks. This list of agents could be

expanded by adding efficiency agents that help to

coordinate, prioritize and schedule other personal

agents work in order to achieve higher performance

results. That is especially important in perspective of

mobile devices used as the basic hardware platform

for PKMS as they have limited resources and

connection time with the Internet or with other type

of network.

The era of intelligent agents approaches quite

fast even though still are being used rather simple

agents. However despite usage of these relatively

simple agents there are quite good options to

develop an agent-supported environment for

knowledge worker in the PKMS. In Figure 1 is

depicted proposed knowledge worker’s agent

environment. Solid directed lines denote data,

information and knowledge flows. Doted directed

lines denote possible connections between involved

agents.

5 CONCLUSIONS AND FUTURE

PERSPECTIVES

Nowadays are being done first movements towards

online community where intelligent agents will

support individuals in their knowledge work by

helping to get a better grasp on knowledge and

resources located out there on the Web. In particular

the Semantic Web is considered to be the way to go

as the regular Web is missing common uniform data

and information encoding language and common

ontology to represent knowledge. Thus it is

understandable to humans, but not to agents. On

contrary the Semantic Web is the right environment

for intelligent agents, which enables them to help

individuals in better management of their personal

knowledge. Agents will team up in groups to

achieve better performance by working as one whole

unit thus outperforming single intelligent agents.

Another future perspective lays in the idea that

part of agents in the proposed knowledge worker’s

environment could be mobile agents. That would be

especially beneficial in case of using mobile devices.

They have limited memory and processing resources

as well as connections to network are unstable,

KMIS 2009 - International Conference on Knowledge Management and Information Sharing

336

which is very true in remote areas. Thus individual,

for example, could dispatch agent with a task and

reconnect back to network just after a week to find

out the status.

In either way proposed knowledge worker’s

agent-based environment is being seen as a source

for potential direction of creating more enhanced

PKMS. It is also believed to serve as a foundation

for researchers to perform investigation in different

domains like mobile learning, personal business or

healthcare where proposed environment in context

of personal knowledge management approach could

be beneficial to apply.

REFERENCES

AOS Group, 2009. Agent Technology, What are Software

Agents? Retrieved May 30

from, http://www.agent-

software.com/autonomy_and_agents/technology/what

_are_software_agents.html.

Apshvalka, D., 2004. Personal Knowledge Management.

In ECITE’04 Proceedings of the 11th European

Conference on Information Technology Evaluation.

Amsterdam, Netherlands, 17–22.

Apshvalka, D., Grundspenkis, J., 2005. Personal and

Organizational Knowledge Management as a Driving

Force for Business Process Effectiveness. In

Proceedings of the International Conference on

Information Technologies for Business. Vilnius

University, Kaunas, 9–14.

Barth, S., 2000. The Power of One, Knowledge

Management Magazine. Retrieved May 30

from,

http://www.quantum3.co.za/KMM%20Article%20Dec

2000.htm.

Bradshaw, J. M., 1997. Software Agents, AAAI Press. 2

edition.

Dalkir, K., 2005. Knowledge Management in Theory and

Practice, Butterworth-Heinemann. Oxford.

Davenport, T.H., Prusak, L., 2000. Working knowledge:

how organizations manage what they know, Harvard

Business School Press, Boston, Massachusetts.

Davenport, T.H., 2005. Thinking for a living: how to get

better performance and results from knowledge

workers, Harvard Business School Press. Boston,

Massachusetts.

Drucker, P.F., 1959. The Landmarks of Tomorrow,

Harper. New York.

Drucker, P.F., Garvin, D., Leonard, D., 1998. Harvard

business review on knowledge management, Harvard

Business School Press. Boston, Massachusetts.

Ellis, C., Wainer, J., 2002. Groupware and Computer

Supported Cooperative Work, In: Multiagent Systems,

A Modern Approach to Distributed Artificial

Intelligence (Waiss, G., Ed.). MIT Press,

Massachusetts, 425-458.

Grundspenkis, J., 2003. Development of Hybrid Intelligent

Systems: Integration of Structural Modeling,

Intelligent Agent and Knowledge Management

Techniques. In Scientific Proceedings of Riga

Technical University, 5th series, Computer Science,

Applied Computer Systems. RTU Publishing, Riga.

Vol. 17, 7-30.

Higgison, S., 2004. “Your say: personal knowledge

management”, Inside Knowledge, 7(7). Retrieved May

from, http://www.ikmagazine.com/.

Knapik, M., Johnson, J., 1998. Developing intelligent

agents for distributed systems: exploring architecture,

technologies, and applications, McGraw-Hill. New

York.

Lange, D., Oshima, M., 1999. Seven good reasons for

mobile agents, Communications of the ACM. March

42(3), 88-89.

Nwana, H., 1996. Software Agents: An Overview.

Knowledge Engineering Review, Cambridge

University Press, 11(3) September, 1–40.

Padgham, L., Winikoff, M., DeLoach, S., 2008. A Unified

Graphical Notation for AOSE. In AOSE’08, 9th

International Workshop on Agent-Oriented Software

Engineering at AAMAS’08 The 7th International Joint

Conference on Autonomous Agents and Multi-Agent

Systems. Estoril, Portugal, 1-12.

Pickett J. P., 2000. The American Heritage Dictionary of

the English Language, Houghton Mifflin. 4

edition.

Quintas, P., 1999. Quoted in: Open Eye - Head Back to

the Business Cafe, The Independent, London,

February 4, Retrieved May 30

from,

http://www.independent.co.uk/news/education/educati

on-news/open-eye-head-back-to-the-business-cafe-

1068608.html.

Tiwana, A., 2002. The Knowledge Management Toolkit:

Orchestrating It, Strategy, and Knowledge Platforms,

Prentice Hall. Upper Saddle River.

Tsui, E., 2002. Technologies for Personal and Peer-to-Peer

(P2P) Knowledge Management, CSC Leading Edge

Forum, Technical Report. Australia.

Vidal, J., Buhler, P., Huhns, M., 2001. Inside an Agent.

IEEE Internet Computing, February, 82–86.

Wiig, K. M., 2004. People-focused knowledge

management: how effective decision making leads to

corporate success, Butterworth-Heinemann. Oxford.

Wooldridge, M., 1999. Intelligent Agents, In: Multiagent

Systems, (Waiss, G., Ed.), MIT Press. Massachusetts,

425-458.

Wooldridge, M., Jennings, N. R., 1995. Intelligent agents:

Theory and practice. The Knowledge Engineering

Review, 10(2), 115–152.

PERSPECTIVES ON USAGE OF AGENTS IN PERSONAL KNOWLEDGE MANAGEMENT

337