Optimum peace maintenance amongst monitored communities is needed for sustainable and social development of the communities and society. The maintenance of peace with the application of correct strategies should be able to deliver maximum degree of trust and strength of relations among the communities. This study presents STES, an expert system that utilizes a biologically inspired novel optimization technique of semiotics that imitates the behavior of predators in marking their territories with their odours and physical marks, known as territorial predator scent marking strategies (TPSMS), to obtain appropriate strategies for maintenance of peace. The current study presents the use of game theory and deterministic finite automata (DFA) theory to model and design a strategic rule set for the Expert System to take decisions for maintenance of optimum peace amongst the communities. A DFA is obtained using various peace states as the set of states, and the alphabet set is constructed by modelling a two-person Prisoner’s Dilemma game over TPSMS. A context free grammar is then obtained by employing top-down parsing, which would suggest the proper rules to be included in the rule set of the Expert System for the maintenance of peace and bringing out sustainable development. A key objective in such decision making therefore would be to select the semiotical peace maintenance strategy in a manner that their applicability configuration ensures a high degree of cooperation within often intensely conflicting communities, over a long term resource use scenario.
Key words: Peace, semiotics, prisoner’s dilemma game, deterministic finite automata (DFA), context free grammar, top-down parsing, territorial predator scent marking strategy.
NDFA, Non deterministic finite automata, STES, semiotics expert system
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