Abstract
In this paper we investigate the communication and cooperation phenomenon in Cooperating Distributed Grammar Systems (henceforth CDGSs). In this respect, we define several complexity structures and two complexity measures, the cooperation and communication complexity measures. These measures are studied with respect to the derivation modes and fairness conditions under which CDGSs may work. We deal with trade-offs between time, space, cooperation, and communication complexity of languages generated by CDGSs with regular, linear, and context-free components. Cooperation and communication processes in CDGSs with regular and linear components are of equal complexity. The two (equal) cooperation and communication complexity measures are either constant or linear, as functions of lengths of words in the generated language. The same result holds for the cooperation and communication complexity of q-fair languages generated by CDGSs with regular and linear components. For the case of non-constant communication (cooperation) the time and space used by a nondeterministic multitape Turing machine to recognize weakly q-fair languages are linear, as is the communication (cooperation) complexity. For CDGSs with context-free components the cooperation and communication complexity may be different. These measures are either linear or logarithmic functions, in terms of lengths of words in the generated language. In order to find trade-offs between time, space, cooperation, and communication complexity of languages generated by CDGSs with context-free components we study asymptotic behavior of growth functions characteristic to these measures. We prove that languages generated by CDGSs with context-free components are accepted by nondeterministic multitape Turing machines either in quadratic time, linear space, and with cooperation complexity that varies from logarithmic to linear, or in polynomial or exponential time and space, and linear cooperation complexity.