This study investigates how the appearance and behavior of virtual agents influence human reactions during immersive interactions in virtual reality. Participants engaged in two interactive games—a word-matching task and an iterated Prisoner’s Dilemma—with virtual partners that varied in their degree of humanlikeness and dominance-related behavior. Behavioral responses, encompassing cooperation patterns and posture changes (based on video recordings), as well as self-reported mind attribution (agency and experience) and emotional data were examined. Results show that hybrid-looking (uncanny) agents triggered greater eeriness and postural contraction among participants, indicating discomfort, though not increased threat or reduced likability. Mind attribution—particularly agency and experience—was positively associated with likability, challenging earlier theoretical claims. In the Prisoner’s Dilemma, women showed higher cooperation and forgiveness rates, especially toward robot-looking agents. Together, the findings suggest that agent appearance and attributed mental capacities influence how participants evaluate and respond to virtual partners.

The current study had two main goals—evaluation of the impact of robot stimuli presentation type (virtual reality vs. on-screen simulation) and investigation of the relation between essentialism beliefs and the uncanny valley effect. The experiment involved a virtual café in which participants confronted four characters ranging from robotic to humanlike. The results showed that robotic characters were rated more eerie than humanlike characters. The robotic character with moderate humanlikeness received the highest eeriness rating, which was interpreted by us as evidence of the uncanny valley effect. Contrary to previous research’s suggestion, participants assessed the humanlikeness and eeriness of characters in the same manner in VR and on-screen. Our results show the importance of essentialism beliefs in attitudes toward the most eerie artificial agents. Strong beliefs in the uniqueness of human nature deepen the uncanny valley effect. Additionally, groups with and without previous knowledge of the uncanny valley effect did not differ in their assessments of variables related to this phenomenon.

The main aim of this paper is to provide a characterization of the response space for questions using a taxonomy grounded in a dialogical formal semantics.As a starting point we take the typology for responses in the form of questions provided in (Łupkowski and Ginzburg, 2016).This work develops a wide coverage taxonomy for question/question sequences observable in corpora including the BNC, CHILDES, and BEE, as well as formal modelling of all the postulated classes.Our aim is to extend this work to cover all responses to questions.We present the extended typology of responses to questions based on a corpus studies of BNC, BEE and Maptask with include 506, 262, and 467 question/response pairs respectively.We compare the data for English with data from Polish using the Spokes corpus (205 question/response pairs).We discuss annotation reliability and disagreement analysis.We sketch how each class can be formalized using a dialogical semantics appropriate for dialogue management.