MATS Alumnus
Rohan Subramani
Collabortators
Jack Foxabbott, Rohan Subramani, Francis Rhys Ward
Citations
Abstract
Multi-agent influence diagrams (MAIDs) are probabilistic graphical models which represent strategic interactions between agents. MAIDs are equivalent to extensive form games (EFGs) but have a more compact and informative structure. However, MAIDs cannot, in general, represent settings of incomplete information -- wherein agents have different beliefs about the game being played, and different beliefs about each-other's beliefs. In this paper, we introduce incomplete information MAIDs (II-MAIDs). We define both infinite and finite-depth II-MAIDs and prove an equivalence relation to EFGs with incomplete information and no common prior over types. We prove that II-MAIDs inherit classical equilibria concepts via this equivalence, but note that these solution concepts are often unrealistic in the setting with no common prior because they violate common knowledge of rationality. We define a more realistic solution concept based on recursive best-response. Throughout, we describe an example with a hypothetical AI agent undergoing evaluation to illustrate the applicability of II-MAIDs.
Weird Generalization and Inductive Backdoors: New Ways to Corrupt LLMs
Authors:
Jorio Cocola, Dylan Feng
Date:
December 10, 2025
Citations:
0
AI agents find $4.6M in blockchain smart contract exploits
Authors:
Fellow: Winnie Xiao
Date:
December 1, 2025
Citations:
0
The MATS Program is an independent research and educational initiative connecting emerging researchers with mentors in AI alignment, governance, and security.
Each MATS cohort runs for 12 weeks in Berkeley, California, followed by an optional 6–12 month extension in London for selected scholars.