Workspace and Slipnet

There are some parts of the Copycat architecture that I haven’t touched yet. Namely the Workspace and the Slipnet. That’s mostly due to the fact that I don’t yet know, how they would fit into the system as I envision it. In some way the Workspace is the short term memory of the system and the Slipnet is the long term memory. But only in some way and I think both cannot that easily reused from Copycat as Codelets and the Coderack.

In Copycat the Slipnet is a network of nodes that is not unlike other networks, i.e. typical neural network implementations. Nodes have activation levels and this activation spreads to connected nodes. But unlike a pure neural network “brain,” the Slipnet is not the place where the main action happens. Instead the nodes and their connections capture the (abstract) knowledge that the system has about the domain and the activation levels reflect what Copycat currently considers as important. Highly activated nodes can spawn Codelets, e.g. if the node “successor” is activated, it may spawn Codelets that actively search for more successor groups. Information flows in the other direction by Codelets that do discovers certain structures and then add some activation to the corresponding node (some generic search Codelets are constantly spawned and if they find something they activate a node – which then triggers more targeted Codelets looking for things like that).

The Slipnet in Copycat is (apart from the activation levels) completely static. So it’s not really “memorized memories,” because it has no way to learn, but more “a priory knowledge.”

The workspace is the place where Copycat builds up the structures and representations of its domain. It is a highly dynamic network of nodes, which is constantly modified by the Codelets. It also has some properties that make it very different from the network of the Slipnet (or neural networks). Connections are built up in several stages, i.e. they are first “proposed” and only later (if they survive long enough) “established.” And while two nodes can only be connected by one established connections, there might exist other, contradicting connections at the same time, which are still in the proposed state. That means that Copycat can build up and evaluate an alternate view of the domain without replacing the current view right away, but only when the new view seems better that the old.

The Workspace is also able to build up hierarchic structures of groups and treat those groups as nodes to operate on.

Both of these components need some changes to be used in a NPC brain. There definitely needs to be some notion of learning and memory. The lack of memory is one of the biggest issues I see in current Game AI (it is somewhat emulated by scripting, but in a very limited way). The Slipnet in Copycat only contains very abstract knowledge, e.g. characteristics of platonic letters and such things (instantiations of letters only exist in the Workspace). So putting knowledge like “Fred has red hair and owes me 20 bucks” in there is a very different thing.

The Workspace will also need some adaptions for my use of it. For example spatial information is one important domain that needs to be represented, so a character can find its way around the world and correctly react to its environment. And there are many other things that need modeling, e.g. relations with other characters, dialogs, etc.

I will have to spend much more time thinking about these things. But I’ll leave that for another day (not implying that I could even scratch the surface on a single day).