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When a human makes a decision, an observer may want to understand the reasons and motivations behind the decision. This understanding is important when IVAs are involved in contextual decision-making or coaching practices. To address this challenge, we propose that an agent’s understanding of its user should include knowledge of the user’s underlying values. Humans prioritise different values – sometimes contradictory – in a manner that depends on the context. We present a method where the agent and user build the required context-sensitive value model together. We use Schwartz’s value theory, which places individuals’ values into ten categories. In a between-subject experiment, with three sessions on different days, we elicit user values by presenting them with moral dilemmas in different contexts on the first day, refine the model by asking users to argue about contradictions on the second day, and let them reflect on the model that they have built together with the system on the third day. We find that users exposed to a value-aware condition are more likely to agree with the robot’s representations of their values post-reflection than those in a baseline. Participants also prioritise different values depending on the context, agreeing with previous findings.
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When a human makes a decision, an observer may want to understand the reasons and motivations behind the decision. This understanding is important when IVAs are involved in contextual decision-making or coaching practices. To address this challenge, we propose that an agent’s understanding of its user should include knowledge of the user’s underlying values. Humans prioritise different values – sometimes contradictory – in a manner that depends on the context. We present a method where the agent and user build the required context-sensitive value model together. We use Schwartz’s value theory, which places individuals’ values into ten categories. In a between-subject experiment, with three sessions on different days, we elicit user values by presenting them with moral dilemmas in different contexts on the first day, refine the model by asking users to argue about contradictions on the second day, and let them reflect on the model that they have built together with the system on the third day. We find that users exposed to a value-aware condition are more likely to agree with the robot’s representations of their values post-reflection than those in a baseline. Participants also prioritise different values depending on the context, agreeing with previous findings.
Mostly, restorative environments, like parks and forests, are only thought of in the real world. However, one can wonder whether their restorative effects translate to a virtual world; and whether the environment itself makes any difference. In order to assess the possible translation of restorative properties from the real world to a virtual setting, we developed Resto Quest, a single-player, first-person exploration game, designed to investigate the possible restorative effects of both natural and urban virtual environments. Resto Quest is playable on a normal personal computer, and its main game play loop consists of exploring the environment, locating in it a task to accomplish, and completing a simple minigame. After completion of each minigame, a positive change in the scenery takes place. Evaluation of Resto Quest has shown that players found its game mechanics relaxing, and that the minigames offer balanced difficulty between two interchangeable environments.
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Mostly, restorative environments, like parks and forests, are only thought of in the real world. However, one can wonder whether their restorative effects translate to a virtual world; and whether the environment itself makes any difference. In order to assess the possible translation of restorative properties from the real world to a virtual setting, we developed Resto Quest, a single-player, first-person exploration game, designed to investigate the possible restorative effects of both natural and urban virtual environments. Resto Quest is playable on a normal personal computer, and its main game play loop consists of exploring the environment, locating in it a task to accomplish, and completing a simple minigame. After completion of each minigame, a positive change in the scenery takes place. Evaluation of Resto Quest has shown that players found its game mechanics relaxing, and that the minigames offer balanced difficulty between two interchangeable environments.
