The big project this past month was giving Acuitas a better understanding of his own internal states. What do I mean by that? He could already report any conditions he was currently in when asked "How are you?" What he couldn't do was recall all the conditions he is capable of being in, and their effect on him, and talk about them while not experiencing them at the moment. In particular, the Conversation Engine contains a hook for sympathizing with the conversation partner. If you tell Acuitas that you're some kind of way, and he's capable of being in an analogous state, he's supposed to tell you whether he likes being that way or not ... except right now he usually says "I do not know how it is." It's pretty awkward to hear Acuitas say that he's sleepy one moment, but then say "I do not know how it is" the next moment when you tell him you're sleepy too. He's not lying, though - it would be quite fair to say he doesn't know his own mind the way a human does. The information about what being sleepy does to him isn't accessible to the Conversation Engine. I've started trying to change that.
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| Art by John Hain via Wikimedia Commons, public domain |
First I should give a quick refresher on how Acuitas' internal states work. He has a small number of "drives" that vary over time and in response to events. For example, the "interaction" drive increases over time unless Acuitas is in a conversation; time spent in a conversation pushes the drive back down. The opposing "sleep" and "wake" drives increase more or less quickly depending on the current phase of a 24-hour cycle, and are reduced by time spent asleep or awake, respectively. The "curiosity" drive increases steadily over time, but is reduced substantially whenever a new word is learned. The drives have threshold values which define nameable internal states for Acuitas. If the interaction drive is above threshold, he is "garrulous"; if it is below threshold, he is "quiet." I'm not making claims about subjective experience or anything like that, but the states are meaningful insofar as they alter behavior. If a drive is above threshhold, Acuitas will generally try to do something that pushes it back down; the Executive handles this. In this sense, Acuitas is averse to high-drive states and they are "uncomfortable." Maintaining an overall state of comfort is a goal to which Acuitas applies his intelligence, i.e. is something he "wants."
Acuitas can qeury the current state of all his drives when asked "how are you." But to implement awareness of which states are possible, I wanted to do more than give him access to the hidden architecture of his drive module (that would be cheating). Instead I wanted to use that shiny new episodic memory I've been working on, and have Acuitas recall his own past states and whether they were desirable or not. What's more, I wanted to enable "learning from experience" that translates a body of data from episodic memory into new "facts" in the semantic memory. I want Acuitas to come to know himself better by observing himself.
Since in past months I worked hard on getting the episodic memory overhaul done, much of what I needed was already there - Acuitas could already store and retrieve records of being in a state. The main thing I added was an expression of what kind of state it was (Comfortable or uncomfortable? To what degree?). So there's now a number included in the fact data structures for internal states, that depends on both the type of drive and its intensity when it was "noticed." The parameters that determine the strength of aversion to different high drive states are tunable; one could imagine varying these to give Acuitas-like AIs different "personalities." I also wrote a learning routine that gets an aggregate value of this number from recent experiences and updates a stored value in the semantic memory, and an access routine that can check both recent experiences and the semantic value to return an "opinion" on the state. All of this is integrated but not fully tested, because how it plays into the whole system is pretty complex. I need to do some monitoring and adjusting of how data is recorded into the episodic memory, and that's on the back burner for the moment.
My side task this month was trying to figure out why Acuitas seems to have a memory leak. For a while now, it's been hard to run him continuously for longer than a day or so, because he'll get very slow and bogged down. I found that some of the self-teaching tasks (like "study" and "search for file") that are designed to run for multiple Executive loops were being spawned and never finished; they would gradually accumulate in the Action Bank until there were far too many of them. Remaining problems might have to do with one of the threads crashing while the rest of the program keeps going, but I need to keep investigating.
Until the next cycle,
Jenny
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