Intelligent Software agents have been around now since a few years. But even although this
technique is still young, it looks promising already. Promising, but also rather vague and a bit obscure to many. This thesis' aim was - and is - to provide an overview of what agents are offering now and are expected to offer in the future. For that purpose, practical examples have been given to indicate what already has been accomplished. A model was outlined which can be used to extend, enhance and amplify the functionality (individual) agents can offer. And trends and developments from past and present have been described, and future developments have been outlined.
One of the conclusions that can be drawn from these trends and developments, is that users will be the ultimate test of agents' success. Users will also (albeit indirectly) drive agents' development; that is something that seems to be certain. What is uncertain is whether users will discover, use and adopt agents all by themselves, or whether they will just start to use them because they are (getting) incorporated into a majority of applications. Users may discover more or less on their own how handy, user-friendly and convenient agents are (or how they are not), just like many users have discovered or are discovering the pros and cons of the Internet and the World Wide Web. But it may just as well go like as in the case of Operating Systems and GUIs, where companies with the biggest market share have more or less imposed the usage of certain systems and software.
To get to this stage, however, some important obstacles need to be tackled first. For example: one of the interesting and powerful aspects of agents will be their ability to communicate with other agents, other applications and - of course - with humans. To do this, good and powerful interfaces and communication languages (i.e. protocols) have to be developed. Standards could be of great help here, but it also takes quite some time (at least some years) before these are drawn up. As much as they will help speed up developments from that moment on, the lack of them is likely to slow down developments up till then.
My expectations are that, within foreseeable time (i.e. within five years), enough of these issues will have been sufficiently dealt
with.  The situation for agents can, in a way, be compared to that in the area of Artificial Intelligence in general: critics have been, and still are saying that it is unclear what AI exactly is, what its aims are, and that AI researchers are not able to come up with many concrete techniques or practical (usually meaning: profitable) applications. These critics seem to pass over the fact that, although there may be a number of concepts that still are rather vague or that lack a clear definition, and that there are a lot of pieces missing in its puzzle, AI has managed to make impressive achievements: concepts and techniques like fuzzy logic and neural networks have been used and incorporated into many applications.
| Examples of such services are the
Sift service of Stanford University and IBM's InfoSage.
 better than many conventional programs.
 which does not mean that they have been completely solved, but to such a degree that they do not interfere (much) with further developments.
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