Search Results for author:
Found 4 papers, 3 papers with code
Mitigating Biases in Collective Decision-Making: Enhancing Performance in the Face of Fake News
Individual and social biases undermine the effectiveness of human advisers by inducing judgment errors which can disadvantage protected groups.
Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making
Experts advising decision-makers are likely to display expertise which varies as a function of the problem instance.
Dealing with Expert Bias in Collective Decision-Making
Quite some real-world problems can be formulated as decision-making problems wherein one must repeatedly make an appropriate choice from a set of alternatives.
Dynamic Weights in Multi-Objective Deep Reinforcement Learning
In the dynamic weights setting the relative importance changes over time and specialized algorithms that deal with such change, such as a tabular Reinforcement Learning (RL) algorithm by Natarajan and Tadepalli (2005), are required.
Multi-Objective Reinforcement Learning
reinforcement-learning
