Marcus Hutter - Universal Artificial Intelligence, AGI 2010
Tutorial on Mini-Column Hypothesis in the Context of Neural Mechanisms of Reinforcement Learning - by Randal A. Koene, AGI 2010
Related to M. Hutter - Jurgen Schmidhuber notices that reinforcement learning needs many steps, many decision points, and marks compression progress as an abstract form of reward for cognitive processes:
Jurgen Schmidhuber-Artificial Scientists Artists Based on the Formal Theory of Creativity, AGI 2010
The following one is mostly to get familiar about the state of the art of Virtual Worlds simulations for AGI - it seems pretty primitive... Taking into account also the demos with reinforcement learning agents in other talks, where the agents play simple games such as Pacman, "Pocman" (partially-observable environment), tic-tac-toe or tank games, or the dogs in Ben Goertzel's demo which learn to carry the object back to their master (coordinates of a bounding rectangle)...
I've been speculating about different virtual world systems for AGI seed AI and other intelligent agents experiments myself, but it was some 6 years ago; wished to start experimenting in formalizing so called my "Teenage Theory of Mind and Universe" and testing it in such worlds, but it was for a short time, and it has left as just ideas because of all the other stuff I had to deal with. However I am back, and certainly there's a lot of work to be done in this field.
Ben Goertzel - Using Virtual Agents and Physical Robots for AGI Research
Some funny closing remarks by Marcus and Ben:
Keywords: neural, mini-column, universal, artificial, intelligence, AGI, UAI, УИР, agents, physics, simulations, reinforcement, learning, AIXI, virtual, worlds, simulators
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