"Conventional" AI was coding all the knowledge in Lisp. Then came rule based systems and the AI winter. Neural networks have produced the best results in language, vision, and robotics, now that we have enough computing power to implement them. Now we have real progress in AI. It will be interesting if you come up with something better.
On Sat, May 11, 2019 at 12:10 PM Stefan Reich via AGI <[email protected]> wrote: > I think you are stuck in the "conventional theory". The time is right for > new theories. I'm still on the path to show that there are better ways to > actual AI than neural networks. > > On Sat, May 11, 2019, 08:46 YKY (Yan King Yin, 甄景贤) < > [email protected]> wrote: > >> Also, the control theoretic stuff was removed because I am unable to >> define the reward based on the current state in a *differentiable* way. >> For example, in the game of chess, the reward comes only when checkmate >> occurs (according to the game's official rules), but not when you capture a >> piece of high value (eg xQueen). This problem is known as "sparse reward" >> vs "dense reward" in reinforcement learning: >> [image: Screenshot from 2019-05-07 20-49-22.png] >> The actual reward is a delta-function occurring at the end of the game. >> "Classical" control theory is applicable only when the reward is something >> like the dotted line. >> >> *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/T3cad55ae5144b323-M70d43d0f634f9f444fb31d04> > -- -- Matt Mahoney, [email protected] ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T3cad55ae5144b323-Mca0223b93da442c9d3604e6f Delivery options: https://agi.topicbox.com/groups/agi/subscription
