Thank you. I really enjoy and appreciate your comments. There is no universal problem solver. So for the purpose of building a real AGI, how many problems should our model be able to solve? How big is our problem space?
On Thu, Aug 1, 2019, 8:22 AM Matt Mahoney <[email protected]> wrote: > The human brain cannot solve every problem. There is no requirement for > AGI to do so either. Hutter and Legg proved that there is no such thing as > a universal problem solver or predictor. > > It feels like you could solve any problem given enough effort, but that is > an illusion. In reality you can't read a 20 digit number and recite it > back. The human brain is good at solving problems that improve reproductive > fitness, and that's only because it is very complex with thousands of > specialized structures and a billion bits of inherited knowledge. > > On Wed, Jul 31, 2019, 10:58 PM Mohammadreza Alidoust < > [email protected]> wrote: > >> I may not call the model "a reinforcement learning neural network", >> because nothing is going to be reinforced there. I would rather call it >> "model based decision making" where the model of the world will be >> incrementally completed and more accurate, which then helps in better >> decision making. >> >> The model is in its early stages and must be tested in heavier tasks like >> the ones you mentioned. However, I believe that AGI is an infinite >> problem-space and a real AGI must be able to solve everything. This >> requires further implementations, modifications, time, teamwork, financial >> support, etc. >> >> On Thu, Aug 1, 2019 at 1:34 AM Matt Mahoney <[email protected]> >> wrote: >> >>> Not understanding the math is the reader's problem. It is necessary to >>> describe the theory and the experiments and shouldn't be omitted. >>> >>> The paper describes 3 phases of training a reinforcement learning neural >>> network. The first phase is experimenting with random actions. The next two >>> phases choose the action estimated to maximize reward. They differ in that >>> they use explicit and then implicit memory, although the paper didn't >>> explain these or other details of the learner. >>> >>> I like that the paper has an experimental results section, which most >>> papers on AGI lack. But I think calling it a "AGI brain" is a stretch. It >>> learns in highly abstract models of chemical manufacturing or cattle >>> grazing. It doesn't demonstrate actual AGI or solve any major components >>> like language or vision. >>> >>> On Wed, Jul 31, 2019, 8:01 AM Manuel Korfmann <[email protected]> >>> wrote: >>> >>>> I guess he meant: It’s difficult to understand all these mathematical >>>> equations. Visualizations are better at transporting ideas in a way that >>>> almost everyone can understand easily. >>>> >>>> On 31. Jul 2019, at 13:46, Mohammadreza Alidoust < >>>> [email protected]> wrote: >>>> >>>> Thank you for reading my paper. I wish you success too. >>>> >>>> Could you please explain more about the readership? I am afraid I did >>>> not get the point. >>>> >>>> Best regards, >>>> Mohammadreza Alidoust >>>> >>>> >>>> On Tue, Jul 30, 2019, 2:14 PM Stefan Reich via AGI < >>>> [email protected]> wrote: >>>> >>>>> If someone paid me to go, I'd go... :-) >>>>> >>>>> > http://agi-conf.org/2019/wp-content/uploads/2019/07/paper_21.pdf >>>>> >>>>> I like the stages you define in your paper (infancy, decision making, >>>>> expert). Sounds reasonable. >>>>> >>>>> I pretty much erased mathematical formulas from my brain though, even >>>>> though I have studied those things. These days I prefer to think in >>>>> natural >>>>> language or code. Increases the readership exponentially too. :-) >>>>> >>>>> Many greetings and best wishes to you >>>>> >>>>> >>>>> On Tue, 30 Jul 2019 at 02:13, Mohammadreza Alidoust < >>>>> [email protected]> wrote: >>>>> >>>>>> Dear Stefan Reich, >>>>>> >>>>>> Thank you. I do not know whether submitting my paper before official >>>>>> publication by Springer is against their copyrights or not. I am not sure >>>>>> about their rules. I will ask the authorities when I arrived Shenzhen and >>>>>> inform you. >>>>>> >>>>>> However I recommend not to miss the AGI-19. >>>>>> http://agi-conf.org/2019/ >>>>>> >>>>>> >>>>>> Best regards, >>>>>> Mohammadreza Alidoust >>>>>> >>>>> >>>>> >>>>> -- >>>>> Stefan Reich >>>>> BotCompany.de // Java-based operating systems >>>>> >>>> >>>> *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + delivery > options <https://agi.topicbox.com/groups/agi/subscription> Permalink > > <https://agi.topicbox.com/groups/agi/Tf27122c71ce3b240-Mfffc300bdacc6680bcf63025> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tf27122c71ce3b240-Mc82055636d6abd2a8d971995 Delivery options: https://agi.topicbox.com/groups/agi/subscription
