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07/04/2023
The Inner Sentiments of a Thought
Transformer-based large-scale language models (LLMs) are able to generat...
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06/08/2023
Habits of Mind: Reusing Action Sequences for Efficient Planning
When we exercise sequences of actions, their execution becomes more flue...
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05/26/2023
Reinforcement Learning with Simple Sequence Priors
Everything else being equal, simpler models should be preferred over mor...
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11/12/2021
Catastrophe, Compounding Consistency in Choice
Conditional value-at-risk (CVaR) precisely characterizes the influence t...
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11/12/2021
Two steps to risk sensitivity
Distributional reinforcement learning (RL) – in which agents learn about...
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10/02/2020
Correcting Experience Replay for Multi-Agent Communication
We consider the problem of learning to communicate using multi-agent rei...
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02/11/2020
Static and Dynamic Values of Computation in MCTS
Monte-Carlo Tree Search (MCTS) is one of the most-widely used methods fo...
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01/24/2019
Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning
We investigate how reinforcement learning agents can learn to cooperate....
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10/01/2018
Probabilistic Meta-Representations Of Neural Networks
Existing Bayesian treatments of neural networks are typically characteri...
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03/27/2018
Fast Parametric Learning with Activation Memorization
Neural networks trained with backpropagation often struggle to identify ...
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02/12/2015
Monte Carlo Planning method estimates planning horizons during interactive social exchange
Reciprocating interactions represent a central feature of all human exch...
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02/09/2014
Better Optimism By Bayes: Adaptive Planning with Rich Models
The computational costs of inference and planning have confined Bayesian...
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05/14/2012