Using HMM in Strategic Games

Benevides, Mario R. F.; Lima, Isaque Macalam Saab; Nader, Rafael; Rougemont, Pedro

doi:10.4204/eptcs.144.6

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…Hidden Markov Games (HMG [42]) represent a fusion of Markov Games with Hidden Markov Models (HMMs), enabling the estimation of transition probabilities between hidden type states. In their research, HMGs were applied to predict transitions between hidden type states in a tennis game characterized by stationary transitions.…”

Section: Defenses and Related Workmentioning

confidence: 99%

Limitations of Theory of Mind Defenses against Deception in Multi-Agent Systems

Piazza,

Behzadan,

Sarkadi

2023

Preprint

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The presence of deceptive agents within a multi-agent system can exert a detrimental influence on the performance and stability ofother agents in shared environments. In multi-agent interactions, the utilization of Theory of Mind (ToM) has become a considerable mech-anism for defenses against deception where it can possibly provide defenses with robustness and resilience to adverse effects against diverseforms of deception. ToM is the cognitive process through which an agent ascribes states to other agents, encompassing beliefs, objec-tives, intentions, desires, or any other characteristic. This paper investigates into the effectiveness and inherent limitations of employ-ing ToM-based defenses. We leverage stochastic games and Bayesian games, specifically highlighting formulations of Multi-Agent Reinforce-ment Learning (MARL) to establish the boundaries of ToM as a defense.

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Section: Defenses and Related Workmentioning

confidence: 99%

Limitations of Theory of Mind Defenses against Deception in Multi-Agent Systems

Piazza,

Behzadan,

Sarkadi

2023

Preprint

View full text Add to dashboard Cite

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“…Oneofthemostpopularandthreateningattacksthatmostlyaffectcloud-basedinfrastructureis DenialofService(DoS)/DistributedDenialofService(DDoS)attacks.ADoSattackusuallyhaltsa virtualmachine (Fanetal.,2013) So,theHiddenMarkovModel(HMM)canbeusedasastatisticalmethod(Ariuetal.,2007) (Benevides et al, 2014) in speech recognition, extraction of information and other areas where classificationisrequired.Therefore,itcanalsobeusedforintrusiondetectionasithastheability toeasilymodeltimeseriesbyusingastatefulapproachinwhichtheinternalstatesarehidden.In caseofintrusiondetection,theseseriescanbesequencesofsomeeventsoritcanbeafunctionor commandsthatmayberunningonasinglehostmachine.…”

Section: Introductionmentioning

confidence: 99%

A Hidden Markov Model Combined With Markov Games for Intrusion Detection in Cloud

Narwal

Kumar

Singh

2019

Journal of Cases on Information Technology

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Cloud computing has evolved as a new paradigm for management of an infrastructure and gained ample consideration in both industrial and academic area of research. A hidden Markov model (HMM) combined with Markov games can give a solution that may act as a countermeasure for many cyber security threats and malicious intrusions in a network or in a cloud. A HMM can be trained by using training sequences that may be obtained by analyzing the file traces of packet analyzer like Wireshark network analyzer. In this article, the authors have proposed a model in which HMM can be build using a set of training examples that are obtained by using a network analyzer (i.e., Wireshark). As it is not an intrusion detection system, the obtained file traces may be used as training examples to test a HMM model. It also predicts a probability value for each tested sequence and states if sequence is anomalous or not. A numerical example is also shown in this article that calculates the most optimal sequence of observations for both HMM and state sequence probabilities in case a HMM model is already given.

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Application of the Iterated Prisoner's Dilemma and Evolutionary Game Theory in Siting Nuclear Power Plants in South Korea

Kim¹

2022

International Journal of Mathematical Models and Methods in Applied Sciences

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The quality of an urban living environment largely depends on the planning and development of public facilities, which are often halted or delayed due to the NIMBY (not in my backyard) phenomenon. In such facilities, environmental costs are borne solely by the residents of proximity to the facility, while public goods/services produced by the facility are reaped equally by residents across the greater region, which in turn presents a complex dynamic of public and self-interest. This paper uses repeated games and evolutionary game theory to identify the optimal negotiation strategy for the government when siting nuclear power plant facilities in South Korea. This study simulated a tournament containing 36 selected iterated prisoner's dilemma strategies and considered factors including mean payoff values, payoff matrices, and Axelrod's Ecological Variant to deduce an optimal strategy. The results showed that AON2, a memory-2 strategy of direct reciprocity, would provide the most stable and high return negotiations.

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Using HMM in Strategic Games

Cited by 3 publications

References 4 publications

Limitations of Theory of Mind Defenses against Deception in Multi-Agent Systems

Limitations of Theory of Mind Defenses against Deception in Multi-Agent Systems

A Hidden Markov Model Combined With Markov Games for Intrusion Detection in Cloud

Application of the Iterated Prisoner's Dilemma and Evolutionary Game Theory in Siting Nuclear Power Plants in South Korea

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