AI RESEARCH

Learning from Acceptance: Cumulative Regret in the Game of Coding

arXiv CS.LG

ArXi:2605.09754v1 Announce Type: cross Classical coding-theoretic guarantees often rely on trust assumptions, such as requiring sufficiently many honest nodes compared with adversarial ones. These assumptions are difficult to enforce in open decentralized systems where participants are not centrally certified. At the same time, such environments often contain incentive mechanisms: participants may be rewarded only when their submitted data are accepted and the system remains functional. This changes the role of an adversary.