Saying that there is an agent refers (in my view; definition for this thread) to a situation where future events are in some sense expected to be optimized according to some goals
Omohundro's paper says:
Researchers have explored a wide variety of architectures for building intelligent systems: neural networks, genetic algorithms, theorem provers, expert systems, Bayesian networks, fuzzy logic, evolutionary programming, etc. Our arguments apply to any of these kinds of system as long as they are sufficiently powerful.
It's not obvious to me why any of these systems would be "agents" under your definition. So I guess your definition is too strong. My question stands.
The "sufficiently powerful" clause seems to me like something that should translate as roughly my definition, making implementation method irrelevant for essentially the same reasons. In context, "powerful" means "powerful as a consequentialist agent", and that's just what I unpacked (a little bit) in my definition.
I have stopped understanding why these quotes are correct. Help!
More specifically, if you design an AI using "shallow insights" without an explicit goal-directed architecture - some program that "just happens" to make intelligent decisions that can be viewed by us as fulfilling certain goals - then it has no particular reason to stabilize its goals. Isn't that anthropomorphizing? We humans don't exhibit a lot of goal-directed behavior, but we do have a verbal concept of "goals", so the verbal phantom of "figuring out our true goals" sounds meaningful to us. But why would AIs behave the same way if they don't think verbally? It looks more likely to me that an AI that acts semi-haphazardly may well continue doing so even after amassing a lot of computing power. Or is there some more compelling argument that I'm missing?