MULTIAGENT AIR COMBAT WITH CONCURRENT MOTIONS

This paper is a new step in the development of the Linguistic Geometry. This formal theory is intended to discover the inner properties of human expert heuristics, which have been successful in a certain class of complex control systems, and apply them to different systems. The Linguistic Geometry relies on the formalization of search heuristics of the highly-skilled human experts, which allow for the decomposition of a complex system into a dynamic hierarchy of subsystems, and thus solve intractable problems by reducing the search dramatically. In this paper we report application of the Linguistic Geometry tools to a new example of a solution of simplified 2D optimization problem for the autonomous robotic vehicles in aerospace environment. The novelty of this example with respect to other Linguistic Geometry applications is that in this multiagent problem some agents can move simultaneously. There are many such problems where human expert skills in reasoning about complex systems are incomparably higher than the level of modern computing systems. At the same time there are even more areas, especially in the aerospace problem domain, where advances are required but human problem-solving skills can not be directly applied. For example, there are problems of tactics planning and automatic control of autonomous agents such as aerospace vehicles, space stations and robots with cooperative and opposing interests functioning in a complex, hazardous environment. Reasoning about such complex systems should be done automatically, in a timely manner, and often in a real time. Moreover, there are no highly-skilled human experts in these fields ready to substitute for robots (on a virtual model) or transfer their knowledge to them. There is no grand-master in robot control, although, of course, the knowledge of existing experts in this field should not be neglected – it is even more valuable. Due to the special significance of these problems and the fabulous costs of mistakes, the quality of solutions must be very high and usually subject to continuous improvement.