I do not speak much but follow the discussions of the list. I am currently an undergraduate student at Lund university in Sweden. At the moment, I'm primarily still learning and touching different subjects.
I am interested in primarily three things: * Optimal algorithms for arbitrary well and ill-formed problems. For ill-formed problems, I do not even know if it makes sense. Well-formed problems are to some extent solved, which is very exciting. There are some restrictions with the current algorithms, such as optimal decisions w.r.t. to limited resources or utility functions contingent the used resources. By optimal I obviously mean the maximal expected outcome of any policy w.r.t. to the resource-dependent utility function. I do not only mean the question of what resources are neede for the maximal expected utility (EU*) without any resource restrictions for particular problems. The greatest goal of AI, I do not consider only to achieve human-level intelligence but optimal and either a formal way to handle ill-formed problems or limited resources would be a grand next step. * Proper handling of ill-formed/ill-posed problems. This seems tricky to me. Many times, statistics may be applied to learn about the problem, generalize, simplify and solve the simpler problem. Many tests today, mind you, most of what you discuss on this list, is sampling where one attempts to learn about the problem at hand. A lot of complications arise with this and I feel even more lost on how to apporach the first point in this context. * The formal computer science foundations of decision science algorithms ( i.e. non-mimicry AI). This class is broader than machine learning and does include for instance logical inference. A further division would be 1) AI problems on a wit. Such as logical inference and heuristics that does not generalize from observations. 2) generalization/machine learning. Here, heuristic approaches are justified through statistics even if it is not explicitly in the motivation. The difference from regular AI vs. ML would be the heuristic classes. A less important goal would also be to formalize all heuristic approaches with a statistical foundation. Any comments, criticism or pointers much appreciated. On 3/26/07, DEREK ZAHN <[EMAIL PROTECTED]> wrote:
David Clark writes: >Everyone on this list is quite different. It would be interesting to see what basic interests and views the members of this list hold. For a few people, published works answer this pretty clearly but that's not true for most list members. I'll start. I'm a dilettante. I am most interested in spending my time wondering how small a chunk of "code" could implement AGI. I believe that the physical and cultural structure of a human being's environment provide the vast majority of the complexity of a human mind, and there may be a rather small amount of complexity (necessary "code") needed to leverage that environment. I'm interested in figuring out exactly what this small core would need to do. I guess something like 10^16 operations working on 10^16 bits of information is roughly what's required for "human equivalence", given operations and bits defined roughly in current computer terms. I think those numbers are just about average for those interested in AGI who have made public guesses. Since there are still so many orders of magnitude between any hardware I can get my hands on and the amount required, I'm content to just think about things for now and don't feel a big need to write lots of code right now. I do think it is crucial for us to build AGI before it can run at human equivalence in real-time, so we can understand it and hopefully avoid scenarios like Yudkowski describes where self-improvement rapidly spirals out of control. If it turns out that a Commodore 64, Pentium4-based pc, or BlueGene are already powerful enough for AGI, we could be in trouble. What about the rest of you, what are your interests? ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?list_id=303
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