We present an information-theoretic framework to learn fixed-dimensional...
Responsibility attribution is a key concept of accountable multi-agent
d...
Actual causality and a closely related concept of responsibility attribu...
We study reward design strategies for incentivizing a reinforcement lear...
Blame attribution is one of the key aspects of accountable decision maki...
This survey article has grown out of the RL4ED workshop organized by the...
We study a dynamic model of Bayesian persuasion in sequential decision-m...
We study defense strategies against reward poisoning attacks in reinforc...
We study a security threat to reinforcement learning where an attacker
p...
News diversity in the media has for a long time been a foundational and
...
We study a security threat to reinforcement learning where an attacker
p...
We consider a two-agent MDP framework where agents repeatedly solve a ta...
What is the best way to define algorithmic fairness? There has been much...
We study a problem of optimal information gathering from multiple data
p...
We study minimal single-task peer prediction mechanisms that have limite...
We analyze different notions of fairness in decision making when the
und...