If so, and if it could be made at all practical, I think that would be a major breakthrough. The current stories about wirehead-avoidance are not terribly convincing, IMO. Which is not to say that there's not a solution - just that we do not yet really know how to implement one.
An ADT agent cares about some utility function which is independent of its experiences
That is kind-of impossible, though. All our knowledge of the world necessarily comes to us through our senses.
I had a brief look at it again. It seems very expensive. When making a decision, it is painful to start by integrating over all possible copies of agents who might be "like you". In short, it doesn't look remotely like what is most likely to come first.
Update 2011-06-28. OK, I finally figured out what you were talking about above - and it turns out that I don't agree with it at all. The "LessWrong"-style decision theories that I am aware of so far don't have any impact on the wirehead problem at all - as far as I can see.
All our knowledge of the world necessarily comes to us through our senses.
Yes, but an agent can understand that it's fixed utility function which refers to the state of the entire universe is not maximized by allowing itself to be deceived.
Daniel Dewey, 'Learning What to Value'
Abstract: I.J. Good's theory of an "intelligence explosion" predicts that ultraintelligent agents will undergo a process of repeated self-improvement. In the wake of such an event, how well our values are fulfilled will depend on whether these ultraintelligent agents continue to act desirably and as intended. We examine several design approaches, based on AIXI, that could be used to create ultraintelligent agents. In each case, we analyze the design conditions required for a successful, well-behaved ultraintelligent agent to be created. Our main contribution is an examination of value-learners, agents that learn a utility function from experience. We conclude that the design conditions on value-learners are in some ways less demanding than those on other design approaches.