Hello, > How would you see a very basic agent as being > able to accomplish all of what you said, in RunRev?
This is one of those "64,000 dollar questions" of AI, but let me just allude, for now, to several MC features that could be useful to us : * MetaCard multi-platform deployment (serverside as well as clientside) makes it a very good candidate for widely distributed agent-based achitectures. As good as Java for what we need, but a *LOT* less complicated than Java for most people. * MC's web-savvy-ness makes it an excellent for crafting web-based agents. This is *extremely* relevant given the importance and spread of the Internet. Every agent based system currently in the running, and all those that will follow, need to be web-savvy. There's no get around this constraint. Without the web, you're out of the game from the very start. * In case some of you don't know, MC's web-savvy-ness is not limited to getting URLs. It goes as deep as creating your own web protocol with [secure] sockets. Instead of HTTP or FTP, we could have an agent protocol; something like this : agent://ufp.uqam.ca/dispatcher The proverbial HTTP protocol was designed to accomodate the many needs of hypertext. FTP was optimized for quick file transfers. And so on... Our AGENT protocol would be optimized for knowledge-exchange and agent-coordination. * The "try .. on error.." control structure which allows a handler to catch its own errors and execute meta-code that can fix the problem, allowing the agent to continue with its on-going mission. As a bonus, it also optimizes performance because it always tries to do the best thing first & handles exceptional stuff exceptionally. No un-necessary "if .. then .." pre-processing. * MC features GREP, which allows agents to smartly parse informally-structured information. Locating links inside web pages with the help of GREP is a cinch, which means that it s very very easy to create a hyper-bot, with MC, that traverses the web as easily as any web-indexing bot can. * Several people on this list have crafted some XML-RPC stuff from within MC. I am presently seeking some help in this regard. Ian Gordon was kind enough to point me in the right direction, albeit I've not had enough time to follow up on it yet. My development team is about to embark on the open-source development of some XML-RPC capabilities for MetaCard, including compatibility with the blogger API. With the latter our agents will be able to inter-operate with blogs, wikis, and other opensource wares that are very hot right now. In general, XML-RPC capability will allow us to send Remote Procedure Calls to any program that supports XML-RPC, e.g. *LOTS* > Do you typically need self-modifying code? Not necessarily. On the one hand, self-modifying code is so dangerous that most operating systems don't allow em to do this. On the other hand, life and intelligence are self-modifying... it's what gives these 'systems' their strength, you might say. I don't have any easy answer[s] for this issue [yet] ... except one, perhaps. We script the agents so that their 'thinking' is data-driven, and their behavior determined at runtime. In plain english, we script the hooks, but all of the [operational] info is stored in external files, fetched by URL, etc. Only these external sources change; not the program itself. > If so, aren't RR's script limits > somewhat of a problem. Yes. That's why an open source (LGPL) alternative to the MC engine, e.g. FreeCard, is still a crucial project for the xCard community. > Also, how do IA's differ with Neural Nets? > Expert Systems? Genetic Algorithms? Neural Nets, Expert Systems, Genetic Algorithms are some of the ways that cognitive scientists have attempted to model intelligence with computers. They each have their merits and their shortfalls. None are as effective as we would like them to be. But there is no need to *choose* one at the expense of the others. Each agent's internals are irrelevant at the social level. One agent can be an expert system, another implemented as a neural net, etc. At the social level, where the agents interact with each other, a diversity of implementations is even desirable, because then the agents could collaborate in such a way that they complement each other, e.g. the shortfalls of one agent systemically compensated for by the different strengths of the other agents. > I'd be interested in seeing a very simple IA > implemented to do something (find the best > price online for a product) using RR. Do you > know of such an example? I have a HyperCard-based example of a forward-chaining rule-based inference engine. It's very very simple to understand and to use; so much so that you may not see how ths is different from traditional scripting. Here is the URL just in case your interested : http://pan.uqam.ca/cgi-bin/usemod/wiki.pl?Electronics Are we having fun yet ? ;-)) --> I am. Alain F The UFP guy __________________________________ Do you Yahoo!? Yahoo! Finance: Get your refund fast by filing online. http://taxes.yahoo.com/filing.html _______________________________________________ metacard mailing list [EMAIL PROTECTED] http://lists.runrev.com/mailman/listinfo/metacard