[Lisa_seminaires] [Lisa_montreal] [Tea Talk] Bradly Stadie (UC Berkeley) Wed Feb 21 3:00PM PCM Z220

Yoshua Bengio yoshua.umontreal at gmail.com
Mer 21 Fév 14:59:44 EST 2018


Starting now!

2018-02-20 12:20 GMT-05:00 Michael Noukhovitch <mnoukhov at gmail.com>:

> *CORRECTION*: the room is Pavilion Claire McNicoll Z220
>
> On Tue, Feb 20, 2018 at 12:14 PM Michael Noukhovitch <mnoukhov at gmail.com>
> wrote:
>
>> Sorry for the lateness, please note this talk is a normal tea talk and it
>> is *tomorrow!* If you want to meet with the speaker, please email me and
>> I'll set it up!
>>
>> This week we have *Bradly Stadie* from *UC Berkeley* giving a talk on *Wednesday
>> Feb 21* at *3:00PM* in room *AA1360*.
>>
>> See you there!
>> Michael
>>
>> *TITLE* Towards Quickly Learning Agents
>>
>> *KEYWORDS *Meta-learning, Reinforcement Learning, Imitation Learning
>>
>>
>> *ABSTRACT*We consider the problems of meta reinforcement learning,
>> wherein the goal is to train agents that can learn new tasks quickly. We
>> suggest 5 major sub-problems that are crucial for enabling quickly learning
>> agents: Exploration, Imitation, Hierarchy/Planning, Credit Assignment, and
>> Control.
>>
>> The talk will examine the sub-problems of exploration and imitation and
>> their interplay with quickly learning agents in more depth. In particular,
>> we examine:
>>
>> 1) Third Person Imitation: which enables agents to imitate other agents
>> that differ significantly from themselves.
>> 2) One Shot Imitation: which enables a robot to see a single video of a
>> demonstration and copy the demonstrated behavior.
>> 3) E-MAML: a meta-RL algorithm that achieves significantly better
>> exploration than previous meta-RL algorithms.
>>
>> *BIO*
>> Bradly Stadie is a PhD student at UC Berkeley in Pieter Abbeel’s lab.
>> Previously, he spent 2 years working at Open AI under Ilya Sutskever.
>> Bradly’s work has focused on the fields of exploration, imitation, and meta
>> learning with applications to games, robotics, and causal inference. Prior
>> to his interest in AI, Bradly studied mathematics at the University of
>> Chicago, where his work focused on representation theory of locally compact
>> groups and stochastic differential equations.
>>
>>
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