A redundancy-based filtering Q-learning algorithm makes all agents converge almost surely to optimal values under Byzantine attacks by enforcing a new verifiable topological condition on the communication graph.
Resilient multiagent reinforcement learning with function approxi- mation
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.MA 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Fully Byzantine-Resilient Distributed Multi-Agent Q-Learning
A redundancy-based filtering Q-learning algorithm makes all agents converge almost surely to optimal values under Byzantine attacks by enforcing a new verifiable topological condition on the communication graph.