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This paper addresses how the cognitive theory and machine learning methods are combined for predicting human behavior. Prediction of human behavior is a complex task. Researchers addressing this task proposes behavior models using statistical methods and rationality theory such as machine learning algorithms. This paper addresses how the potential cognitive theory and machine learning methods are combined in using by providing and predicting human behavior. We discussed two theory focal points theory and aspiration adaptation theory can be used in combination with machine learning algorithm to simplify the task and understanding the behavior. These two approaches are combined and compared in two domains. In simple domain, both machine learning models and psychological models give clear predictions and results. While in complex domains, the results states that psychological models’ results are not cleared and in learning models are also inaccurate. To overcome this problem, the hybrid model is introduced which helps in understanding of how people behave and at the same time how they wouldn’t behave reducing the space helping machine learning algorithms in searching the accurate behavior models. Hybrid model with cognitive models and machine learning have contributed in models which predicted behavior accurately as compared to machine learning models/cognitive models alone. The future researches must work in these directions using hybrid models for successful prediction of behavior.

Due to globalized scenario, employing diversified workforce is a necessity for every organization but to manage such diversified workforce is also a big challenge for management. The rapid growth in the Banking industry has posed several challenges such as workforce diversity which is a natural phenomenon that has both negative and positive impacts on employee performance depending on how well it is managed. The study covered the bank's branches in Agra specifically, whose zonal offices lie in Agra. The study tackled areas of workforce diversity, effects of diversity on employee performance and how workforce diversity can be managed so as to maximize the positive outcomes and minimize the negative outcomes. The respondents were the managers and employees of the Bank. To make the study more focused, the researchers have selected certain variables of diversified workforce. The study reveals that there is a positive correlation between age and productivity of organization. The employees whose age is above 50 are very much effective in client handling. But if we talk about the bank's work which is related with physical activeness, youngsters are much more contributing towards the bank's productivity. If we talk about the qualification of employees and productivity then we find that, the qualification of the bank employees and their performance are associated significantly with each other. Next diversity factor is the experience of various employees, the results shows that the working experience of the bank employees and their performance are associated significantly with each other. Another variable is interpersonal relationship. Research shows that if the employees are satisfied at their workplace and are having cordial and harmonious relations with other employees, they can contribute positively towards the productivity of an organization. Recent studies have also shown a strong correlation between good diversity practices and profits.

The present paper focuses on the relationship between Optimum stimulation level and exploratory tendencies. The main objective of the paper is to analyze the relationship between Optimum Stimulation Level and Exploratory Tendencies- Risk Taking, Innovative Behavior, Variety Seeking and Curiosity- motivated behavior.