Including Conversational Agents into Structured Hybrid 3D Virtual Environments

Structured Hybrid 3D Virtual Environments are 3D virtual spaces where staff (organisational) software agents support human users in their task achievement. These systems are characterized by: i) being hybrid, so that humans and software agents can interact; and ii) being structured and task oriented, so that interactions are regulated by a subjacent Organisation Centered Multi Agent System (OCMAS)-an Electronic Institution (EI). The contribution of this paper is to include task-oriented conversational staff bots (i.e. the embodiment of staff agents in the 3D environment) that communicate with users by using natural language. With this aim, we extend the Artificial Intelligence Mark-up Language (AIML) with special tags to enable complex task-oriented conversations whose flow needs to consider both the states of the conversation and the ontology related to the task. We evaluate the usability of our conversational proposal and compare it to a previous command-based interaction system. Results show the conversational approach presents a higher user satisfaction than the command-based one. Moreover, in average, it also performs better in terms of efficiency, effectiveness and errors

Facilitating Natural Conversational Agent Interactions: Lessons from a Deception Experiment

This study reports the results of a laboratory experiment exploring interactions between humans and a conversational agent. Using the ChatScript language, we created a chat bot that asked participants to describe a series of images. The two objectives of this study were (1) to analyze the impact of dynamic responses on participants’ perceptions of the conversational agent, and (2) to explore behavioral changes in interactions with the chat bot (i.e. response latency and pauses) when participants engaged in deception. We discovered that a chat bot that provides adaptive responses based on the participant’s input dramatically increases the perceived humanness and engagement of the conversational agent. Deceivers interacting with a dynamic chat bot exhibited consistent response latencies and pause lengths while deceivers with a static chat bot exhibited longer response latencies and pause lengths. These results give new insights on social interactions with computer agents during truthful and deceptive interactions

Facilitating Natural Conversational Agent Interactions: Lessons from a Deception Experiment

This study reports the results of a laboratory experiment exploring interactions between humans and a conversational agent. Using the ChatScript language, we created a chat bot that asked participants to describe a series of images. The two objectives of this study were (1) to analyze the impact of dynamic responses on participants’ perceptions of the conversational agent, and (2) to explore behavioral changes in interactions with the chat bot (i.e. response latency and pauses) when participants engaged in deception. We discovered that a chat bot that provides adaptive responses based on the participant’s input dramatically increases the perceived humanness and engagement of the conversational agent. Deceivers interacting with a dynamic chat bot exhibited consistent response latencies and pause lengths while deceivers with a static chat bot exhibited longer response latencies and pause lengths. These results give new insights on social interactions with computer agents during truthful and deceptive interactions