154 citations · 487 across the 15 of their papers we have counts for
15 papers
The Inner Sentiments of a Thought
Chris Gagne, Peter Dayan
Transformer-based large-scale language models (LLMs) are able to generate highly realistic text. They are duly able to express, and at least implicitly represent, a wide range of s…
Reinforcement Learning with Simple Sequence Priors
Tankred Saanum, Noémi Éltető, Peter Dayan +2
Everything else being equal, simpler models should be preferred over more complex ones. In reinforcement learning (RL), simplicity is typically quantified on an action-by-action ba…
Catastrophe, Compounding & Consistency in Choice
Chris Gagne, Peter Dayan
Conditional value-at-risk (CVaR) precisely characterizes the influence that rare, catastrophic events can exert over decisions. Such characterizations are important for both normal…
Two steps to risk sensitivity
Chris Gagne, Peter Dayan
Distributional reinforcement learning (RL) -- in which agents learn about all the possible long-term consequences of their actions, and not just the expected value -- is of great r…
Correcting Experience Replay for Multi-Agent Communication
Sanjeevan Ahilan, Peter Dayan
We consider the problem of learning to communicate using multi-agent reinforcement learning (MARL). A common approach is to learn off-policy, using data sampled from a replay buffe…
Static and Dynamic Values of Computation in MCTS
Eren Sezener, Peter Dayan
Monte-Carlo Tree Search (MCTS) is one of the most-widely used methods for planning, and has powered many recent advances in artificial intelligence. In MCTS, one typically performs…