We describe an initial prototype of a holodeck-like environment that we have created for the Mission Rehearsal Exercise Project. The goal of the project is to create an experience learning system where the participants are immersed in an environment where they can encounter the sights, sounds, and circumstances of realworld scenarios. Virtual humans act as characters and coaches in an interactive story with pedagogical goals.

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In this paper, we examine the motivations for research on cognitive architectures and review some candidates that have been explored in the literature. After this, we consider the capabilities that a cognitive architecture should support, some properties that it should exhibit related to representation, organization, performance, and learning, and some criteria for evaluating such architectures at the systems level. In closing, we discuss some open issues that should drive future research in this important area. Key words: cognitive architectures, intelligent systems, cognitive processes 1

This paper promotes social role awareness as a desirable capability of animated agents, that are by now strong affective reasoners, but otherwise often lack the social competence observed with humans. In particular, humans may easily adjust their behavior depending on their respective role in a socio-organizational setting, whereas their synthetic pendants tend to be driven mostly by attitudes, emotions, and personality. Our main contribution is the incorporation of `social filter programs' to mental models of animated agents. Those programs may qualify an agent's expression of its emotional state by the social context, thereby enhancing the agent's believability as a conversational partner or virtual teammate. Our implemented system is entirely webbased and demonstrates socially aware animated agents in an environment similar to Hayes-Roth's Cybercaf'e. Keywords believability, social agents, human-like qualities of synthetic agents, social dimension in communication, affective reaso...

Abstract. The goal of Interactive Pedagogical Drama (IPD) is to exploit the edifying power of story while promoting active learning. An IPD immerses the learner in an engaging, evocative story where she interacts with realistic characters. The learner makes decisions or takes actions on behalf of a character in the story, and sees the consequences of her decisions. The story’s characters are realized by autonomous agents. We discuss IPD in the context of Carmen’s Bright IDEAS (CBI), a multimedia title designed to teach problem solving skills to mother’s of pediatric cancer patients. CBI was an exploratory arm of a clinical trial and here we discuss key creative and technical aspects of the design and results from that arm.

The effectiveness of simulation-based training for individual tasks -- such as piloting skills -- is well established, but its use for team training raises challenging technical issues. Ideally, human users could gain valuable leadership experience by interacting with synthetic teammates in realistic and potentially stressful scenarios. However, creating human-like teammates that can support flexible, natural interactions with humans and other synthetic agents requires integrating a wide variety of capabilities, including models of teamwork, models of human negotiation, and the ability to participate in face-to-face spoken conversations in virtual worlds. We have developed such virtual humans by integrating and extending prior work in these areas, and we have applied our virtual humans to an example peacekeeping training scenario to guide and evaluate our research. Our models allow agents to reason about authority and responsibility for individual actions in a team task and, as appropriate, to carry out actions, give and accept orders, monitor task execution, and negotiate options. Negotiation is guided by the agents' dynamic assessment of alternative actions given the current scenario conditions, with the aim of guiding the human user towards an ability to make similar assessments.

This paper describes the results of a research project aimed at implementing a ‘realistic ’ 3D Embodied Agent that can be animated in real-time and is ‘believable and expressive’: that is, able to communicate with coherency complex information, through the combination and the tight synchronisation of verbal and nonverbal signals. We describe, in particular, how we `animate ' this Agent (that we called Greta) so as to enable her to manifest the affective states that are dynamically activated and de-activated in her mind during the dialog with the user. The system is made up of three tightly interrelated components:- a representation of the Agent Mind: this includes long and short-term affective components (personality and emotions) and simulates how emotions are triggered and decay over time according to the Agent’s personality and to the context and how several emotions may overlap. Dynamic belief networks with weighting of goals is the formalism we employ to this purpose;- a mark-up language to denote the communicative meanings that may be associated with dialog moves performed by the Agent;- a translation of the Agent’s tagged move into a face expression, that combines appropriately the available channels (gaze direction, eyebrow shape, head direction and movement etc). The final output is a 3-D facial model that respects the MPEG-4 standard and uses MPEG-4 Facial Animation Parameters to produce facial expressions. Throughout the paper, we illustrate the results obtained, with an example of dialog in the domain of ‘Advice about eating disorders’. The paper concludes with an analysis of advantages of our cognitive model of emotion triggering and of the problems found in testing it. Although we did not yet complete a formal evaluation of our system, we briefly describe how we plan to assess the agent’s believability in terms of consistency of its communicative behavior.

In this paper we introduce ALMA – A Layered Model of Affect. It integrates three major affective characteristics: emotions, moods and personality that cover short, medium, and long term affect. The use of this model consists of two phases: In the preparation phase appraisal rules and personality profiles for characters must be specified with the help of AffectML – our XML based affect modeling language. In the runtime phase, the specified appraisal rules are used to compute real-time emotions and moods as results of a subjective appraisal of relevant input. The computed affective characteristics are represented in AffectML and can be processed by sub-sequent modules that control the cognitive processes and physical behavior of embodied conversational characters. ALMA is part of the VirtualHuman project which develops interactive virtual characters that serve as dialog partners with human-like conversational skills. ALMA provides our virtual humans with a personality profile and with real-time emotions and moods. These are used by the multimodal behavior generation module to enrich the lifelike and believable qualities.

The paper presents requirements for the design of unscripted (emergent) dramas based on research into role-playing games. It considers the FearNot! demonstrator in antibullying education as a sample implementation, describing the architecture of its affectively driven intelligent autonomous characters. It presents a comparative evaluation of the unscripted version against an earlier scripted version, examines related work and further development of the emergent narrative approach.

We present a framework for handling emotional variations in a speech-based natural language generation system for use in the MRE virtual training environment.