Modeling with Non-cooperative Agents: Destructive and Non-Destructive Search Algorithms for Randomly Located Objects

The problem of plastic anti-personal mine detection is well known. These devices are typically 75mm in diameter and between 25mm to 50mm in thickness. Some types contain no metal, but their explosive (RDX, TNT) can be considered as a dielectric material with a dielectric constant between 3.5 and 4.0. This electromagnetic property enables a radar to identify mines. It is true that the radars operating “through the air” provide a high detection rate. However, in the case of operating “into the ground”, the problems are significant and inherently reduce performance. Target identification is done in the presence of the air-ground interface, which usually produces a higher amplitude signal than an anti-personal mine Chignell (1998). This context can justify why the difficulties of detecting anti-personal mines are formidable. A family of search mobots controlled by a new algorithm proposed in this research could be a solution1 for operating on the ground. In this Chapter we2 address the general question of what is the best strategy to search efficiently for randomly located objects (target sites). We propose a new agent based algorithm for searching in an unpredictable environment. The originality of our work consists in applying a non-cooperative strategy, namely the distributed Goore Game model, as opposed to applying the classical collaborative and competitive strategies, or individual strategies. This research covers both the destructive search and the non-destructive search. The first occurs when the agent visits the target only one time. The latter can be performed in either of the two cases if the target becomes temporarily inactive or if it leaves the area. The proposed algorithm has two versions: one when the agent can move with a step equal to unity and the other when the step of the agent follows a Levy flight distribution. The second version is inspired by the work of A.M. Reynolds et al. Reynolds (2006a;b; 2007; 2008a;b; 2009); Reynolds & Rhodes (2009); Rhodes & Reynolds (2007) where he braced the use of Levy processes when resources are sparsely distributed within unpredictable environments. The Chapter is organized as follows. The Goore Game is presented in the next section. In Section 2 we introduce the terminology of the Learning Automata, methodology used for