Security in multiagent systems by policy randomization

Praveen Paruchuri, Milind Tambe, Fernando Ordóñez, Sarit Kraus

Research output: Contribution to conferencePaperpeer-review


Security in multiagent systems is commonly defined as the ability of the system to deal with intentional threats from other agents. This paper focuses on domains where such intentional threats are caused by unseen adversaries whose actions or payoffs are unknown. In such domains, action randomization can effectively deteriorate an adversary's capability to predict and exploit an agent/agent team's actions. Unfortunately, little attention has been paid to intentional randomization of agents' policies in single-agent or decentralized (PO)MDPs without significantly sacrificing rewards or breaking down coordination. This paper provides two key contributions to remedy this situation. First, it provides three novel algorithms, one based on a non-linear program and two based on linear programs (LP), to randomize single-agent policies, while attaining a certain level of expected reward. Second, it provides Rolling Down Randomization (RDR), a new algorithm that efficiently generates randomized policies for decentralized POMDPs via the single-agent LP method.

Original languageEnglish
StatePublished - 2006
Event9th International Symposium on Artificial Intelligence and Mathematics, ISAIM 2006 - Fort Lauderdale, FL, United States
Duration: 4 Jan 20066 Jan 2006


Conference9th International Symposium on Artificial Intelligence and Mathematics, ISAIM 2006
Country/TerritoryUnited States
CityFort Lauderdale, FL


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