Expert-level Decision System

An expert-level decision system is a type of expert system. It is a large-scale weak artificial intelligence, which is neural-net based. In other words it is a learning artificial mind, but one which will only learn about knowledge within set constraints.

They are designed to emulate, or ideally exceed the level of relevant knowledge a human professional in the same field possesses, but only the knowledge within that field. They are not general artificial intelligences (strong AI) and possess no sense of self, no understanding of anything that does not relate to their field of expertise.

The idea behind this particular type of expert system is that because it has instant access to more knowledge than a human expert's mind is likely to be able to recall at any given moment, and is able to directly access huge datasets in a way the human mind cannot, the decision making ability of the system will equal, or exceed the decision making ability of human experts.

In practice, expert-level decision systems are still a bit hit and miss. They are still only expert systems and so can only use data they have been exposed to. Their ability to extrapolate is limited by their programming, and their neural net components are entirely related to absorbing and integrating new data provided to them; not creating it themselves.

See Also: Expert System, Neural Network, Weak AI, Strong AI, General Artificial Intelligence

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Expert-level Decision System

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Level vs Non-Level
For gameworlds, this one. A comparison of the relative benefits of level based experience systems, with a level less system based on individual skill.

Choosing a Setting
?Choosing a setting. It can be a problem for any administrator, and it is my opinion that there is no more pivotal decision when creating a game. Everything one does, everything added and created from beginning to end, will be within the framework of what is chosen now. Such a choice is never easy to make, this decision delaying many potentially great games - indefinitely in some cases.?

Expert System Matches Human Eye in Identifying Artwork
The highly subjective task of critically evaluating artwork for composition, and authorship has always been beyond artificial intelligence systems. It has been believed by some, that it always would be. Times do change indeed.

Machine Learning

This book is an introductory level coverage of AI. Specifically it covers methods and algorithms that allow computer programs to automatically improve through experience. Intended for upper level undergraduate and introductory level graduate courses in machine learning, it is understandably light on content in many areas.

Magic Symbol and Video Conferencing: Expert Help Over Distance
A rudimentary but workable system using magic symbol codes and augmented reality to put an end to hellish support calls. Now, via a videoconference even over a cellphone, the person on the other end can see and work with the hardware causing the problem.

Why Plan?
Most NPC behaviour takes place as a set of preprogrammed directives - the expert system approach. What if, instead of doing it this highly efficient, if a bit limited way, and took a new approach - giving the characters a highly flexible "plan of action" that could change at any moment...

Prosthetics
An introductory-level overview of the field of prosthetic limb replacement, and the level of development it is reaching.

Standards > PACS
Picture Archiving and Communications System, or PACS is a digital image standard, used increasingly in medicine. A basic level standard, it is often in place before more advanced standards like DICOM.

Fortune Telling
In the wake of Sony's decision to open a virtual goods marketplace, this article looks at what is in store for the industry, and virtual nations in general.

Advancement Revisited
A detailed look at advancement systems for gameworlds, can be found in this article, going beyond the relative skill level comparison route, to discussing why hiding skill level gains will not work, the problems with comparative scoring for skill levels, and proposing a solution which offers greater incentive to learn, on the part of the player ? at the cost of more thought required by the developer.

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