Optimising of support plans for new graduate employment market using reinforcement learning

Mori, Kazuhiko; Kurahashi, Setsuya

doi:10.1504/ijcat.2011.041654

Cited by 8 publications

(3 citation statements)

References 7 publications

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“…Certain works use algorithms from graph theory for optimal pairing of workers and job positions [24] or multi-agent systems [25] to model defined areas of the labor market.…”

Section: Current Approaches In the Area Of Job-matchingmentioning

confidence: 99%

Decision Support System for Evaluating Suitable Job Applicants

2021

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This paper describes a novel approach in the area of evaluating suitable job applicants for various job positions, and specifies typical areas of requirement and their usage. Requirements for this decision-support system are defined in order to be used in middle-size companies. Suitable tools chosen were fuzzy expert systems, primarily the inference system Takagi-Sugeno type, which were then supplied with implementation of methods of variant multi-criteria analysis. The resulting system is a variable tool with the possibility to simply set the importance of individual selection criteria so that it can be used in various situations, primarily in repeated selection procedures for similar job positions. A strong emphasis is devoted to the explanatory module, which enables the results of the expert system to be used easily. Verification of the system on real data in cooperation with a collaborating company has proved that the system is easily usable.

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“…Certain works use algorithms from graph theory for optimal pairing of workers and job positions [24] or multi-agent systems [25] to model defined areas of the labor market.…”

Section: Current Approaches In the Area Of Job-matchingmentioning

confidence: 99%

Decision Support System for Evaluating Suitable Job Applicants

2021

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“…Of the 35 articles, only four articles are related to student performance. These articles relate to simulation of online peer support (de Bakker, van Bruggen, Jochems, & Sloep, 2011), students' grades (Wejnert, 2006), and graduate employment (Cai, 2013;Mori & Kurahashi, 2011).…”

Section: What Specific Dynamics Do Existing Abms Applications Cover In He?mentioning

confidence: 99%

“…The simulation results show that three micro-level processes lead to significant increases in overall grades, and significant reductions in the effort required achieving those grades. Mori and Kurahashi (2011) developed an ABMS application to improve the effectiveness of job matching processes for new graduates. The simulation indicates Profit Sharing and Actor-Critic methods, two types of reinforcement learning contained in the model, effectively support students' job-hunting activities and raise the findingemployment proportion of the entire graduate employment market.…”

Section: What Specific Dynamics Do Existing Abms Applications Cover In He?mentioning

confidence: 99%

A systematic review of agent-based modelling and simulation applications in the higher education domain

Blackmore

2015

Higher Education Research & Development

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This paper presents the results of a systematic review of agent-based modelling and simulation applications in the higher education (HE) domain. Agent-based modelling is a 'bottom-up' modelling paradigm in which system level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro). This approach to considering the behaviour of systems of interacting 'agents' has been applied to a wide variety of domains. Of particular interest are the ways that ABMS applications have been used to further understand the dynamics of the HE domain. We conduct a systematic review of literature to analyse publications by year, role of the simulator, development stage of the models, and any associated validation. We also identify areas for future work, which includes an emphasis on validating existing and future models, detailed description of simulations to allow replication and further development, and the use of agent-based models in other contexts within the increasingly complex HE domain.

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Model Prediction and Inverse Simulation

Kurahashi

2018

Innovative Approaches in Agent-Based Modelling and Business Intelligence

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Optimising of support plans for new graduate employment market using reinforcement learning

Cited by 8 publications

References 7 publications

Decision Support System for Evaluating Suitable Job Applicants

Decision Support System for Evaluating Suitable Job Applicants

A systematic review of agent-based modelling and simulation applications in the higher education domain

Model Prediction and Inverse Simulation

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