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Found 7 papers, 1 papers with code
Societal and technological progress as sewing an ever-growing, ever-changing, patchy, and polychrome quilt
Artificial Intelligence (AI) systems are increasingly placed in positions where their decisions have real consequences, e. g., moderating online spaces, conducting research, and advising on policy.
A theory of appropriateness with applications to generative artificial intelligence
Humans navigate a multi-scale mosaic of interlocking notions of what is appropriate for different situations.
Soft Condorcet Optimization for Ranking of General Agents
This optimal ranking is the maximum likelihood estimate when evaluation data (which we view as votes) are interpreted as noisy samples from a ground truth ranking, a solution to Condorcet's original voting system criteria.
Rethinking Teacher-Student Curriculum Learning through the Cooperative Mechanics of Experience
Teacher-Student Curriculum Learning (TSCL) is a curriculum learning framework that draws inspiration from human cultural transmission and learning.
Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization
While reward maximization is at the core of RL, reward engineering is not the only -- sometimes nor the easiest -- way for specifying complex behaviors.
LOCO: Adaptive exploration in reinforcement learning via local estimation of contraction coefficients
We offer a novel approach to balance exploration and exploitation in reinforcement learning (RL).
Active Domain Randomization
Our experiments show that domain randomization may lead to suboptimal, high-variance policies, which we attribute to the uniform sampling of environment parameters.
