Dr. Mark Humphrys

School of Computing. Dublin City University.

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Research - The World-Wide-Mind - Draft Proposal

The World-Wide-Mind:
Draft Proposal

Mark Humphrys
Dublin City University, School of Computing

This is Technical Report no. CA-0301. See full reference.

This is a first draft of ideas for the WWM system, as at Feb 2001.
Further revisions will not appear here, but rather in a number of forthcoming papers.


In the first part of this paper, a change in methodology for the future of AI and Adaptive Behavior research is proposed. It is proposed that researchers construct their agent minds and their agent worlds as servers on the Internet. 3rd parties will use these servers as components in larger systems. In this scheme, any user on the Internet will be able to (a) select multiple minds from different remote "mind servers", (b) select a remote "Action Selection server" to resolve the (inevitable) conflicts between these minds, and (c) run the resulting constructed "society of mind" in the world provided on another "world server". All this without necessarily having to consult with the server authors. This constructed society may now also be presented as just another primitive mind server, ready for reuse by others as a component in a larger system.

From the current situation of isolated experiments we will move to a situation where not only can researchers use each other's agent worlds, but they can also use each other's agent minds as components in larger systems. Servers may call other servers, and it is expected that 3rd parties will continuously write wrappers and filters for existing mind servers, overriding and modifying their default behaviour (to produce new, co-existing mind servers). None of this necessarily means that the mind being used ever leaves its server (or that its insides are even made public). Hence the term, the "World-Wide-Mind" (WWM), referring to the fact that the mind may be physically distributed across the world, with parts of the mind at different remote servers.

Part of the motivation for the WWM is that if the AI project is to be successful, it may be too big for any single laboratory to complete. So it will be necessary both to decentralise the work and to allow a massive and ongoing experiment with different combinations of components (so that we are not locked into any particular layout of decentralisation). Central to the WWM scheme is the expectation that researchers will not agree on how to divide up the AI work, and so components will overlap and be duplicated.

Previous work by this author [Humphrys, 1997] introduced models of mind where competition took place between extremely incompatible components, and where the mind could survive communications failure with or even complete loss of a number of such components. The WWM idea grew out of this work, and this paper shows how these previous models are the type of models we need in the WWM.

In the second part of this paper, we move towards an implementation of the WWM by trying to define the set of queries and responses that the servers should implement. Clients (including other servers) may then implement any general-purpose algorithm to drive the servers through repeated use of these queries. In our initial implementation, we consider schemes of very low-bandwidth communication. For instance, schemes where the competition among multiple minds is resolved across the network using numeric weights, rather than by explicit reasoning and negotiation. It is possible that this low-bandwidth protocol may be more suitable to sub-symbolic AI than to other branches of AI, and that other protocols may be needed for other branches of AI. It is suggested that it may be premature in some areas of AI to attempt to formulate a "mind network protocol", but that in the sub-symbolic domain it could at least be attempted now. Whether the protocol presented here is adopted or not, the first part of this paper (the need for a protocol) stands on its own.

Finally, we suggest a lowest-common-denominator approach to actually implementing these queries, so that current AI researchers have to learn almost nothing in order to put their servers online. As the lowest-common-denominator approach we suggest the transmission across ordinary CGI of queries and responses written in XML.

Keywords - World-Wide-Mind, WWM, Network Minds, Distributed Models of Mind, Society of Mind, Distributed AI, autonomous agent architectures, Action Selection, Internet, client-server, HTTP, CGI, XML, AIML.


Part 1

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