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Designing and delivering a training to a nonprofit audience is not about extreme content delivery or putting together a PowerPoint and answering questions. If you want to get results, you need to think about instructional design and learningtheory. And, there is no shortage of learningtheories and research.
Defining the Theoretical Reward Learning Research Agenda In one sentence, the aim of this research agenda is to develop a mature theoretical foundation for the field of reward learning (and relevant adjacent areas). Some other notable options include e.g. multi-objective RL, temporal logic, or different kinds of non-Markovian rewards.
This year we are presenting over 100 papers and are actively involved in organizing and hosting a number of different events, including workshops and interactive sessions.
We attentively respond to requests and purposefully use different modes of feedback to inform program design from our comment board, social media outlets, conversations and observations both inside and outside the museum, creative feedback at events such as our Show and Tell Booth and online visitor surveys specific to our programs.
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So when youre doing mechanistic interpretability, you have some claim about how the model behaves, and how the model actually behaves might be a bit different than this, but if your understanding is any good, itll be pretty close. Can you tell us: in this case of max of n, roughly, what are you doing to get different kinds of proofs?
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