The Remote Associates Test (RAT, CRA) is a classic creativity test used to measure creativity as a function of associative ability. The RAT has been administered in various different languages. Nonetheless, because of how embedded in language the test is, only a few items are directly translatable, and most of the time, the RAT is created a new in each language. This process of manual (and in two cases, computational) creation of RAT items is guided by the researchers' understanding of the task. This paper focuses on the question of whether RAT datasets administered in different languages within the literature are comparable. To answer this question, datasets acquired using different RAT stimuli are analyzed qualitatively and quantitatively. Kruskal-Wallis tests are conducted to find out whether there is a significant difference between any of the datasets for a given time frame. Pairwise Mann-Whitney post-hoc tests are then used to find out which pairs are different. Significant differences are observed between 18 dataset pairings regarding Accuracy and between 16 in terms of Response Time. The potential sources of these differences are discussed, together with what this means for creativity psychometrics and computational vs. manual creation of stimuli.

The Remote Associates Test (RAT) is a widely used test for measuring creativity, specifically the ability to make associations. The Remote Associates Test normally takes a linguistic form: given three words, the participant is asked to come up with a fourth word associated with all three of them. While visual creativity tests do exist, no creativity test to date can be given in both a visual and linguistic form. Such a test would allow the study of differences between various modalities, in the context of the same creative process. In this paper, a visual version of the well-known Remote Associates Test is constructed. This visual RAT is validated in relation to its linguistic counterpart.

Problem-solving, creativity and spatial reasoning are high level abilities of cognitive systems with high potential for synergies. However, they have been treated separately by different fields. This special issue presents research work on these topics, aiming to observe their interrelations in order to create theoretical approaches, methodologies and computational tools to advance work on creativity and spatial problem-solving in cognitive systems.

The Remote Associates Test is a well‐established measure, frequently used to assess individuals’ creative abilities, as a function of the ability to elicit remote associates. The nature of the involved associative processes is still poorly understood. This hampers a deeper understanding of the creative process, rendering it difficult to determine what factors are controlled for, when the RAT is employed. We report an experiment that sheds further light on the nature of the associative process by manipulating (a) the frequency with which a pair of items are associated as associative strength, and (b) the probability of reaching the answer given the strength and the spread. Experimental results indicate a clear and surprisingly separate influence of frequency and probability on accuracy and response times. Frequency and probability both are thus factors that need to be included in the modeling process and controlled for when using the RAT to assess creativity.

The Remote Associates Test (RAT) is a measure of associative ability, which is often regarded as essential for creative thinking. The most commonly used version of the test is the compound RAT. However, many RAT items do not translate directly in different languages. Additionally, a linguistic measure cannot be used to measure visual associative ability. A visual measure for associative ability that is similar to the RAT would be a useful tool for cross-cultural investigations of creativity. The present study investigated the relationship between the linguistic and a newly developed visual version of RAT in Russian and Finnish native speakers (for both samples n = 67). Both linguistic and visual measures showed good internal reliabilities in both samples (Cronbach's α = 0.73-0.84). The mean score in the visual task was slightly higher for the Finnish sample. The correlation between the two measures was stronger in the Russian sample (r = 0.56) compared to the Finnish sample (r = 0.28). These results are discussed in relation to linguistic and cultural differences between the samples.

Re-representation is a critical ability to (i) understanding human creative problem solving, and (ii) modeling computational cognitive systems able to support or perform creative problem solving tasks on their own. This paper proposes a unified multi-level cognitive approach to investigating re-representation: the study of sensory-based, concept-based and problem template based possible forms of re-representations in an integrated manner. Descriptions and explanations of each level prepare the ground for further computational modeling. A study is deployed in order to explore the relationship between the various tasks proposed to reflect re-representation. A significant correlation between the investigated tasks is discovered. Two previous studies from the literature are replicated. A new strong and significant relationship between the Pattern Meanings Test and the Alternative Uses Test is observed.

The Remote Associates Test (RAT) is a classical creativity test developed by Mednick and Mednick in 1967. RAT problems and their norms so far exist only in a few languages, including English, Dutch, Japanese and Italian. In this paper, we describe our process of constructing a set of Remote Associates Test problem in Romanian. 63 native speaking Romanian participants have solved this set. The set of items shows high internal consistency. Normative data pertaining to each problem is provided, together with a description of RAT problems peculiarities in Romanian.

Cognitive science and cognitive psychology have long used creativity tests to measure and investigate the relationships between creativity, creative problem solving and other cognitive abilities. Implementing cognitive systems that can model and/or solve creativity tests can shed light on the cognitive process, and presents the possibility of building much more precise creativity measuring tools. This paper describes four cognitive AI systems related to the Remote Associates Test (RAT) and their contributions to creativity science. comRAT-C is a system that solves the RAT, correlating with human performance. comRAT-G reverse engineers this process to generate RAT queries with a high degree of parameter control. fRAT generates functional RAT queries, resurrecting a theoretical concept proposed by researchers many decades ago. The visual RAT takes advantage of the formal conceptualization necessary for computational implementation, to expand the RAT to the visual domain. All the cognitive systems and generated RAT queries have been successfully validated with human participants and have contributed in improving creativity modeling and measuring tools.

This poster presents an initial set of observations on different strategies of solving a creativity test under difficult conditions. Human participants show a propensity to answer with a stronger associate of one or two of the query items, while less frequently responding with a weaker but more inclusive associate of all three. Additionally, solvers sometimes responded with answers that held functional relations to the query item(s), even when instructed to provide a compound solution. These strategies of falling back on semantic or strongly occurring associates are explored, together with some of their implications on the design of adaptive mechanisms for cognitive systems.

Using games to model, measure and increase creativity in children and adults would be a very engaging path to social impact and empirical progress. This paper proposes an approach to reframe the new and popular board game Codenames using associative creativity principles. The Remote Associates Test (RAT) is a test measuring creativity as a function of associative ability. comRAT-C is a previous computational cognitive system that can solve the RAT using associative and convergence principles. In this paper, we formalise Codenames using associative principles from comRAT-C. A way to computationally model and measure the difficulty of Codenames is proposed. We discuss whether Codenames or a future variant of it can be used in creativity research.