Allocating Educational Resources through Happiness Maximization and Traditional CSP Approach

An instance of an Educational Resources Allocation (ERA) problem is the distribution of a set of students in different laboratories. This can be a complex and dynamic problem if non-quantitative considerations (i.e. how close the final allocation is to the student preferences or desires) are involved in the decision process. Traditionally, different approaches based on Constraint-Satisfaction techniques and Multi-agent negotiation have been applied to the general problem of Resource Allocation. This paper shows how a Multi-agent approach can be used to model and simulate the assignment of sets of students to several predefined laboratories, by using their preferences to guide the allocation process. This approach aims at finding new solutions that try to satisfy individual student needs with no knowledge about the general allocation problem. The paper shows some experimental results and a comparison, between a CSP-based solution modeled in CHOCO, a CSP Java-based library, and a Multi-agent model implemented using MASON, a multi-agent simulation platform.