Examination of toy preferences – play skills and aggression tendencies of 60–72-month-old children

The purpose of this research is the examination of toy preferences and play skills of 60–72-month-old children according to aggression tendencies. The study group of this research includes 307 people consisting of 60–72-month-old children continuing their kindergarten in Cukurova district of Adana and their parents. As data collection tools, ‘Personal Information Form’, ‘Informed Consent Form’ and ‘Toy Preference Form’ were prepared by the researchers to learn the toy preferences of the children after reviewing the relevant thesis. The ‘Aggression Tendency Scale’ and ‘Play Skill Scale’ were used. In accordance with the studies carried out, it is seen that the play skills of the participants differ according to the aggression tendency levels in all sub-dimensions of the aggression tendency scale and there is a negative interrelation. In addition to this, it is seen that the most preferred toys among the children with a high aggression tendency level in all sub-dimensions of the aggression tendency scale are the war toys. It is suggested to make attempts for the determination of the variables effective on the aggression tendency levels and play skills, realisation of more scientific researches regarding the issue of aggression that might have devastating results in social terms and the development of the play skills of the experts working with the children. Keywords: Toy preference, play skill, aggression tendency.

Advancements in Dueling Bandits

The dueling bandits problem is an online learning framework where learning happens ``on-the-fly'' through preference feedback, i.e., from comparisons between a pair of actions. Unlike conventional online learning settings that require absolute feedback for each action, the dueling bandits framework assumes only the presence of (noisy) binary feedback about the relative quality of each pair of actions. The dueling bandits problem is well-suited for modeling settings that elicit subjective or implicit human feedback, which is typically more reliable in preference form. In this survey, we review recent results in the theories, algorithms, and applications of the dueling bandits problem. As an emerging domain, the theories and algorithms of dueling bandits have been intensively studied during the past few years. We provide an overview of recent advancements, including algorithmic advances and applications. We discuss extensions to standard problem formulation and novel application areas, highlighting key open research questions in our discussion.