Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

On the nature and role of intersubjectivity in communication

We outline a theory of human agency and communication and discuss the role that the capability to share (that is, intersubjectivity) plays in it. All the notions discussed are cast in a mentalistic and radically constructivist framework. We also introduce and discuss the relevant literature

Using Noninvasive Brain Measurement to Explore the Psychological Effects of Computer Malfunctions on Users during Human-Computer Interactions

In today’s technologically driven world, there is a need to better understand the ways that common computer malfunctions affect computer users. These malfunctions may have measurable influences on computer user’s cognitive, emotional, and behavioral responses. An experiment was conducted where participants conducted a series of web search tasks while wearing functional nearinfrared spectroscopy (fNIRS) and galvanic skin response sensors. Two computer malfunctions were introduced during the sessions which had the potential to influence correlates of user trust and suspicion. Surveys were given after each session to measure user’s perceived emotional state, cognitive load, and perceived trust. Results suggest that fNIRS can be used to measure the different cognitive and emotional responses associated with computer malfunctions. These cognitive and emotional changes were correlated with users’ self-report levels of suspicion and trust, and they in turn suggest future work that further explores the capability of fNIRS for the measurement of user experience during human-computer interactions

Improving video game conversations with trope-informed design

This paper examines tropes in video games pertaining to conversations between player characters and Non-Player Characters (NPCs). Drawing from the fields of pragmatics and Conversation Analysis we show how these tropes differ from real, face-to-face conversations. We demonstrate how politeness theory (how to avoid unsociable, face-threatening behaviour) can help us understand when and why conversations with NPCs disrupt player immersion. Based on these insights we propose alternative designs to improve immersion. We call this approach Trope-Informed Design: tropes are tools that can make or break a player’s experience. Considering how and when to perpetuate, subvert, or transcend tropes can help guide designers in improving their game mechanics

Improving video game conversations with trope-informed design

This paper examines tropes in video games pertaining to conversations between player characters and Non-Player Characters (NPCs). Drawing from the fields of pragmatics and Conversation Analysis we show how these tropes differ from real, face-to-face conversations. We demonstrate how politeness theory (how to avoid unsociable, face-threatening behaviour) can help us understand when and why conversations with NPCs disrupt player immersion. Based on these insights we propose alternative designs to improve immersion. We call this approach ‘Trope-Informed Design’: tropes are tools that can make or break a player’s experience. Considering how and when to perpetuate, subvert or transcend tropes can help guide designers in improving their game mechanics

"Shouldn't I use a polarquestion?" Proper Question Forms Disentangling Inconsistencies in Dialogue Systems

This work reports on the description of a specific class of clarification requests, adopted for the negotiation of pieces of information part of the common ground for argumentation strategies in human-machine interaction. Two studies are carried out to prove the adequateness of a specific form of polar question in a specific pragmatic situation, where a presupposition is contradicted by a new evidence. Whereas the first one proves the appropriateness of the negative form, the second one also demonstrate how the use of such a form, in the aforementioned pragmatic situation, can affect the principle of robustness, in terms of observability and recoverability, important in human–machine interaction applications. Given the results obtained in the two studies, dialogue systems with such capabilities are, therefore, a desirable goal, as they are expected to lead to improved usability and naturalness in conversation. For this reason, I present here a system capable of detecting conflicts and of using argumentation strategies to signal them consistently with previous observations

Define, Evaluate, and Improve Task-Oriented Cognitive Capabilities for Instruction Generation Models

Recent work studies the cognitive capabilities of language models through psychological tests designed for humans. While these studies are helpful for understanding the general capabilities of these models, there is no guarantee that a model possessing sufficient capabilities to pass those tests would actually use those capabilities in performing real-life tasks. In this work, we formulate task-oriented cognitive capabilities, which are human-like cognitive capabilities that language models leverage to perform tasks. These capabilities are (i) the ability to quickly generate good candidate utterances (the search capability) (ii) the ability to predict how a listener interprets those utterances and choose the most appropriate one (the pragmatic capability). We design an evaluation scheme for comparing these capabilities of a language model with those of a human. Applying this scheme to examine various models in a navigation instruction generation problem, we find that their pragmatic capability is severely lacking. This insight leads us to augment them with better models of the listener and obtain a significant boost of 11% in success rate in guiding real humans. Our work advocates for having a principled procedure for aligning language models with humans that involves (i) formulating task-oriented capabilities, (ii) devising a method to quantify their deficiency, and (iii) iteratively improving them.Comment: Findings of ACL 202