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Idea generation platforms are increasingly striving to become truly collaborative. Prior research suggests that people are inspired when being exposed to ideas of others. While most platforms defer judgment and separate it from the idea generation phase, we hypothesized that asking participants to rate ideas in the idea generation phase, the increased exposure to other people's ideas would serve as a source of inspiration and motivation and would therefore be preferred to a separate feedback phase.In an explorative study with 26 participants we found that preference on immediate versus deferred judgment of ideas very much diverged. The results of our study suggest that participants that feel already motivated and able are distracted by the integration of feedback, while to others it is highly beneficial in terms of facilitating their idea generation and motivating them further.

Emotions are a fundamental part of everyday life and an important topic in the development of artificial intelligence. We combine a Simultaneous Localization and Mapping algorithm with a model of emotion. The model of emotion is able to generate a mapping from the quantitative figures of the SLAM process to human-like emotions. This enables the robot to communicate its current state towards a human observer using emotional expressions. The paper reports on the design of the model, the result of the affective evaluation during an autonomous path finding process and its comparison to experimental data of a survey.