Collaborative Computers

Collaborative computers are a consequence of graph languages and protocol-free communication.

A graph language like Havel allows end-users to model information and to create the processing instructions that deal with them. These processing instructions are fundamentally interwoven with the information; they can even be part of the information itself. Part of the processing instructions can be workflows that define how concrete entities are to be handled in different scenarios.

Samarai brains allow protocol-free communication; any brain can send arbitrary requests to any other brain, which allows for computer-to-computer communication chains driven by complex workflows. This is facilitated by Havel being a universal language and by its modularity, meaning that workflows can be modeled in a universal, modular way. Havel’s expressiveness allows these workflows to be highly complex, to consider every little facet of the real world.

In praxis, this means that a user can instruct his computer to automatically get a dentist appointment. Or she can let her computer negotiate the best price for the latest gadget. It also means that communities and companies can precisely model their business processes which control highly flexible, automatic business-to-business communications with their customers and partners. At some point we will be able to delegate arbitrary tasks to computers and let them execute them autonomously, much as a human assistant can do.

This post is part of a comprehensive introduction into SRDM, graph languages and Havel.

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