Military Applications of Agent-Based Simulations

Abstract

There continues to be increasing interest from a broad range of disciplines in agent-based and artificial life simulations. This includes the Department of Defense-which uses simulations heavily in its decision making process. Indeed, military conflicts can have many attributes that are consistent with complex adaptive systems-such as many entities interacting with some degree of autonomy, each of which is continually making decisions to satisfy a variety of sometimes conflicting objectives. In this paper, we present three applications of agent-based simulations used to analyze military problems. The first uses the MANA model to explore the ability of the U.S. Army's networkbased Future Force to perform with degraded communications. The second studies how unmanned surface vehicles can be used in force protection missions with the Pythagoras model. The last example examines the standard Army squad size with an integrated effort using MANA, Pythagoras, and the high-resolution simulation JANUS.

Defense and homeland security applications of multi-agent simulations

“…These situations lend themselves to being examined with multi-agent simulation (MAS). Computational experiments using MAS allow insight into the relationships among various agents and their potential strategies and actions Sanchez and Lucas 2002;Cioppa, Lucas, and Sanchez 2004). This paper extends earlier work, but shifts the application emphasis from force effectiveness to counter terror operations and employs more complicated (and bigger) experimental designs.…”

Modeling and Simulation of a DG-Integrated Intelligent Microgrid

“…In general, multi-agent systems were proposed for application in military systems [43,44,45], information retrieval systems [46], decision support systems [47], supply chain [48], transportation [49], communication systems [50] and many more [51,52,53,54,55]. In the context of power systems, multi-agent technologies were applied in a variety of applications, such as to perform power system disturbance diagnosis [56], fault diagnosis [57], power system restoration [58], power system secondary voltage control [59] and power system visualization [60].…”

Effect of Human Biases on Human-Agent Teams

“…This domain for variable e is specified as D e and belongs to the set {0, 1, 2, · · · , R}. The utility for e when a resource, r e ∈ D e , is allocated to e is u e (r e ) = L * I re =0 * (1 − ẽ∈E,ẽ =e I re =rẽ ) + p e (r e ), (1) where p e (r e ) is the preference value of agent e for resource r (soft constraint) and equals 0 when r e is 0. L is a large negative number that represents the penalty for allocating one resource to two different entities (hard constraint) and…”

“…Domains for such applications include search and rescue [5], disaster response [12], military applications [1] and commerce [3]. Researchers envision automating the allocation of shared resources using algorithms such as distributed constraint optimization algorithms (DCOPs) [7].…”