Agents can only learn from axioms. Is this a good model for intelligent behavior?

Unlike the last paper, I’m requiring a topic including a clear statement of the thesis of the paper/research, an outline and a preliminary annotated bibliography.


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Paper Topic
The proof algorithms we’ve seen (resolution, chaining, …) all work by applying logical operations on a set of facts (axioms, predicates, rules, …). This means that the only conclusions that can be drawn by an agent is one that logically follows from a set of axioms. In other words, the only “new” ideas that an agent can have are ones that follow logically from a set of rules (usually given by a human) and its percepts.

Is this a good model for intelligent behavior? Is this how humans get their ideas? Are there any other approaches to designing agents that go beyond these restrictions?

To do this paper well, I’d expect you to look around and see what kinds of agents there are out there, and how they create new facts. Look at some other methods (or expansions to the methods we did in class) for proving things and see how they address this issue (if they do). You’ll also want to look into what we know about how human learning happens (which is a very large topic, so you’ll have to focus on one small area). It’s preferred to look at one or two examples and provide specifics as to how this meets or doesn’t the model of intelligence you have described.

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