There has been a recent resurgence in the area of explainable artificial intelligence as
researchers and practitioners seek to provide more transparency to their algorithms. Much of …

Social science concerns issues on individuals, relationships, and the whole society. The
complexity of research topics in social science makes it the amalgamation of multiple …

Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …

Problems of cooperation--in which agents seek ways to jointly improve their welfare--are
ubiquitous and important. They can be found at scales ranging from our daily routines--such …

Knowledge-based Configuration incorporates knowledge representation formalisms to
capture complex product models and reasoning methods to provide intelligent interactive …

We develop a general framework for social choice problems in which a limited number of
alternatives can be recommended to an agent population. In our budgeted social choice …

Social choice theory concerns the design and formal analysis of methods for aggregating
the preferences of multiple agents. Examples of such methods include voting procedures …

In machine learning, the notion of multi-armed bandits refers to a class of online learning
problems, in which an agent is supposed to simultaneously explore and exploit a given set …

We consider a crowdsourcing database system that may cleanse, populate, or filter its data
by using human workers. Just like a conventional DB system, such a crowdsourcing DB …

We determine the quality of randomized social choice algorithms in a setting in which the
agents have metric preferences: every agent has a cost for each alternative, and these costs …