Author name cluster

Ond

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

4 papers

1 author row

AAMAS Conference 2011 Conference Paper

, a prototype system that demonstrates how agent-based traffic management techniques can be used to improve the security of transit through piracy-affected areas. Combining agent-based modeling and simulation of maritime traffic and novel route planning and vessel scheduling techniques, the system shows the promising potential of agent-based methods for increasing maritime security. AgentC: Agent-based System for Securing Maritime Transit

Michal Jakob
#X159; ej Van
#X11b; k
Branislav Bo
#X161; ansk
yacute;
Ond
#X159; ej Hrstka

Recent rise in maritime piracy prompts the search for novel techniques for addressing the problem. We therefore developed AgentC

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AAMAS Conference 2011 Conference Paper

A Double Oracle Algorithm for Zero-Sum Security Games on Graphs

Manish Jain
Dmytro Korzhyk
Ond
#X159; ej Van
#X11b; k
Vincent Conitzer
Michal P
#X11b; chou

In response to the Mumbai attacks of 2008, the Mumbai police have started to schedule a limited number of inspection checkpoints on the road network throughout the city. Algorithms for similar security-related scheduling problems have been proposed in recent literature, but security scheduling in networked domains when targets have varying importance remains an open problem at large. In this paper, we cast the network security problem as an attackerdefender zero-sum game. The strategy spaces for both players are exponentially large, so this requires the development of novel, scalable techniques. We first show that existing algorithms for approximate solutions can be arbitrarily bad in general settings. We present RUGGED (Randomization in Urban Graphs by Generating strategies for Enemy and Defender), the first scalable optimal solution technique for such network security games. Our technique is based on a double oracle approach and thus does not require the enumeration of the entire strategy space for either of the players. It scales up to realistic problem sizes, as is shown by our evaluation of maps of southern Mumbai obtained from GIS data.

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AAMAS Conference 2011 Conference Paper

Iterative Game-theoretic Route Selection for Hostile Area Transit and Patrolling

Ond
#X159; ej Van
#X11b; k
Michal Jakob
Viliam Lis
Branislav Bo
#X161; ansk
yacute;

A number of real-world security scenarios can be cast as a problem of transiting an area patrolled by a mobile adversary, where the transiting agent aims to choose its route so as to minimize the probability of encountering the patrolling agent, and vice versa. We model this problem as a twoplayer zero-sum game on a graph, termed the transit game. In contrast to the existing models of area transit, where one of the players is stationary, we assume both players are mobile. We also explicitly model the limited endurance of the patroller and the notion of a base to which the patroller has to repeatedly return. Noting the prohibitive size of the strategy spaces of both players, we employ iterative oracle-based algorithms including a newly proposed accelerated scheme, to obtain optimum route selection strategies for both players. We evaluate the developed approach on a range of transit game instances inspired by real-world security problems in the urban and naval security domains.

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AAMAS Conference 2011 Conference Paper

Security Games with Mobile Patrollers

Ond
#X159; ej Van
#X11b; k

To optimally secure large and complex infrastructures against crime activities, a scalable model for optimal defender allocation is needed. Game theory is successfully used to formalize the problem as a two-player game between an attacker and a defender. We consider both player to be mobile and we focus on proper path intersection modeling and we observe the trade-off between fidelity and computational complexity. We search for the a Nash Equlibirium of the game using oracle based algorithms and we evaluate the robustness of the solution in a multi-agent simulation where some assumptions made do not strictly hold.

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