Abstract
Strategic modelling with a panoramic view plays an important role in decision-making problems. It offers the possibility of generating different solutions before making a decision. This is particularly relevant in critical situations. This article addresses the problem of allocating resources, whether financial, material or human, so that it is optimal under a given set of constraints and inter-dependencies with other systems. To do this, existing strategies such as those of Colonel Blotto are studied in order to evaluate them according to some criteria, including the heterogeneity or homogeneity of resources and/or battlefields. Based on the results of these configurations, we propose distributed strategic learning methods to find better resource allocation strategies. The proposed algorithms are implemented under various scenarios, including incomplete information. Case studies are carried out to test the effectiveness of these new strategies compared to previous ones. A complexity analysis of the different algorithms is also presented.
Highlights
Nowadays, information sciences are used in almost all areas of our daily life
Information technologies are, more than ever, a strategic resource for entities and activities such as strategic decision making, learning, modeling, design, development of decision algorithms, integration and validation of strategies.These activities are at the cutting edge of technology and research and involve several fields and skills
The military forces are represented by players, The decisions they make are represented by actions or strategies, The rules of the game define the course of the game, at the end of which, the winner and the loser will be known
Summary
Information sciences are used in almost all areas of our daily life. As a result, information technologies are, more than ever, a strategic resource for entities and activities such as strategic decision making, learning, modeling, design, development of decision algorithms, integration and validation of strategies.These activities are at the cutting edge of technology and research and involve several fields and skills. For the armed forces of a nation, decision-making becomes one of the most important things, because a bad decision would bring huge consequences and heavy losses They are faced with several scenarios, each of which has an implementation and simulation time, allowing them to use the data from this simulation and to make decisions. Strategies for decision-making have been widely explored, but as science evolves day by day, research is devoted to improving existing strategies In this context, we are interested in studying new distributed learning methods for better resource allocation strategies and working on the development and implementation of optimal strategy learning algorithms. We conclude with the discussion outlining interpretations, contribution and limitations of our study directions for further research
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