  Current research in distributed Nash equilibrium (NE) seeking in the partial
information setting assumes that information is exchanged between agents that
are "truthful". However, in general noncooperative games agents may consider
sending misinformation to neighboring agents with the goal of further reducing
their cost. Additionally, communication networks are vulnerable to attacks from
agents outside the game as well as communication failures. In this paper, we
propose a distributed NE seeking algorithm that is robust against adversarial
agents that transmit noise, random signals, constant singles, deceitful
messages, as well as being resilient to external factors such as dropped
communication, jammed signals, and man in the middle attacks. The core issue
that makes the problem challenging is that agents have no means of verifying if
the information they receive is correct, i.e. there is no "ground truth". To
address this problem, we use an observation graph, that gives truthful action
information, in conjunction with a communication graph, that gives (potentially
incorrect) information. By filtering information obtained from these two
graphs, we show that our algorithm is resilient against adversarial agents and
converges to the Nash equilibrium.
