12 papers
Who Is Really Playing? Strategic Interaction in AI-Guided Populations
Jonathan Shaki, Eden Hartman, Sarit Kraus +1
AI systems in general, and Large language models (LLMs), in particular, are increasingly used to provide instructions to many agents who interact with one another. Such shared reli…
Ensemble Self-Training for Unsupervised Machine Translation
Ido Aharon, Jonathan Shaki, Sarit Kraus
We present an ensemble-driven self-training framework for unsupervised neural machine translation (UNMT). Starting from a primary language pair, we train multiple UNMT models that…
Pro-AI Bias in Large Language Models
Benaya Trabelsi, Jonathan Shaki, Sarit Kraus
Large language models (LLMs) are increasingly employed for decision-support across multiple domains. We ask whether these models favor artificial intelligence (AI) itself. We exami…
Coalition Tactics: Bribery and Control in Parliamentary Elections
Hodaya Barr, Eden Hartman, Yonatan Aumann +1
Strategic manipulation of elections is typically studied in the context of promoting individual candidates. In parliamentary elections, however, the focus shifts: voters may care m…
Explaining Decentralized Multi-Agent Reinforcement Learning Policies
Kayla Boggess, Sarit Kraus, Lu Feng
Multi-Agent Reinforcement Learning (MARL) has gained significant interest in recent years, enabling sequential decision-making across multiple agents in various domains. However, m…
Persuading Stable Matching
Jonathan Shaki, Jiarui Gan, Sarit Kraus
In bipartite matching problems, agents on two sides of a graph want to be paired according to their preferences. The stability of a matching depends on these preferences, which in…
Strategic Communication under Threat: Learning Information Trade-offs in Pursuit-Evasion Games
Valerio La Gatta, Dolev Mutzari, Sarit Kraus +1
Adversarial environments require agents to navigate a key strategic trade-off: acquiring information enhances situational awareness, but may simultaneously expose them to threats.…
Bribery for Coalitions in Parliamentary Elections
Hodaya Barr, Yonatan Aumann, Sarit Kraus
We study the computational complexity of bribery in parliamentary voting, in settings where the briber is (also) interested in the success of an entire set of political parties - a…
Control for Coalitions in Parliamentary Elections
Hodaya Barr, Eden Hartman, Yonatan Aumann +1
The traditional election control problem focuses on the use of control to promote a single candidate. In parliamentary elections, however, the focus shifts: voters care no less abo…
Voter Priming Campaigns: Strategies, Equilibria, and Algorithms
Jonathan Shaki, Yonatan Aumann, Sarit Kraus
Issue salience is a major determinant in voters' decisions. Candidates and political parties campaign to shift salience to their advantage - a process termed priming. We study the…
Bayesian Persuasion with Externalities: Exploiting Agent Types
Jonathan Shaki, Jiarui Gan, Sarit Kraus
We study a Bayesian persuasion problem with externalities. In this model, a principal sends signals to inform multiple agents about the state of the world. Simultaneously, due to t…
Heterogeneous Multi-Robot Graph Coverage with Proximity and Movement Constraints
Dolev Mutzari, Yonatan Aumann, Sarit Kraus
Multi-Robot Coverage problems have been extensively studied in robotics, planning and multi-agent systems. In this work, we consider the coverage problem when there are constraints…