I have looked at many Eliza implementations and most only match a single word in the sentence, or a word in the middle and the rest after the match, so I took it a bit further, I can now match stuff like: "I %% flowers **" and also stuff like "I %% and %% flowers **". This would catch several multi-word patterns in between and whatever goes behind flowers. Given that Eliza does pattern matching but the humans employ several words for the same thing if only your Eliza could group by similarities for example by ["love","like","fond of","don't hate","don't dislike"] . Another example: how many Elizas can tell that these are equivalent to a human: ["MAC", "MACs", "Macs", "Mac", "Macintosh", "mac", "macintosh", "apple", "Apple", "Macbook", "mac mini", "Macmini"] ?? So how do you catch different ways of expressing tastes with different nouns, that tell you more or less the same thing ??
Answer: pattern expansion !! I expanded Eliza's linguistic abilities to match similar patterns, you only need to create a pattern list of synonyms and specify that list in another pattern as an expansion pattern like "I ## ##" where ## stands for the synonym list, here is how:
To recreate the above example you would create 3 records in the Eliza file, the first is the pattern and the other 2 are merely variables.
{["I ## ## **"],
["I live inside a computer","I can live inside a Mac","Maybe I reside in a Mac right now"],
{subject,computers,["##1", "##2"],["like","Mac"],[]}},
{["##1"], ["love", "like", "fond of", "don't hate", "don't dislike"], {internal,synonyms,[],[],[]}},
{["##2"],
["MAC","MACs", "Macs", "Mac", "Macintosh", "mac", "macintosh", "apple", "Apple", "Macbook", "Ibook", "Macmini"],
{internal,synonyms,[],[],[]}},
So now the pattern "I ## ##" is expanded against both variables ["##1", "##2"]. which creates in this case 150 patterns in run-time, but your file only required a simple entry and again Eliza returns some values that your AI can now chew on. Those variables can obviously be reused in other patterns and it's needless to say that I will be able to teach her new stuff in run-time.
Things that I find are still needed be it either on Eliza's or the AI's side is to catch specifically nouns and verbs, maybe by matching against another list and trying to find a corresponding context for them, like when your application knows nothing about flowers, but flowers are plants and maybe your AI knows something about plants or maybe it lacks info on Mac's but knows about computers. And Eliza should also be able to ask the user and remember its question. But for the time being, I am quite happy with the implementation, it will suit SMASH well to have NPCs that the user can actually talk to. The current version is stand alone, future ones will likely put their info on KVS* for easy data access and replication.
Cheers,
Sunweaver