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Asymptotically Optimal Agents

Tor Lattimore (ANU)

CS HDR MONITORING AI Group

DATE: 2011-04-27
TIME: 11:30:00 - 12:00:00
LOCATION: RSISE Seminar Room, A105 with Turkish Pide
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ABSTRACT:
Artificial general intelligence aims to create agents capable of learning to solve arbitrary interesting problems. Unfortunately, what it means to be optimal as a general reinforcement learning agent has no clear definitions. I will present two versions of asymptotic optimality, one stronger than the other. I show that no agent can be strong asymptotically optimal and that there exist agents that are weak asymptotically optimal. I also demonstrate that such agents are necessarily incomputable.


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