Modeling human behavior during emergency evacuation using intelligent agents: A multi-agent simulation approach

It is costly and takes a lot of time for disaster employees to execute several evacuation drills for a building. One cannot glean information to advance the plan and blueprint of forthcoming buildings without executing many drills. We have developed a multi-agent system simulation application to aid in running several evacuation drills and theoretical situations. This paper combines the genetic algorithm (GA) with neural networks (NNs) and fuzzy logic (FL) to explore how intelligent agents can learn and adapt their behavior during an evacuation. The adaptive behavior focuses on the specific agents changing their behavior in the environment. The shared behavior of the agent places an emphasis on the crowd-modeling and emergency behavior in the multi-agent system. This paper provides a fuzzy individual model being developed for realistic modeling of human emotional behavior under normal and emergency conditions. It explores the impact of perception and emotions on the human behavior. We have established a novel intelligent agent with characteristics such as independence, collective ability, cooperativeness, and learning, which describes its final behavior. The contributions of this paper lie in our approach of utilizing a GA, NNs, and FL to model learning and adaptive behavior of agents in a multi-agent system. The planned application will help in executing numerous evacuation drills for what-if scenarios for social and cultural issues such as evacuation by integrating agent characteristics. This paper also compares our proposed multi-agent system with existing commercial evacuation tools as well as real-time evacuation drills for accuracy, building traffic characteristics, and the cumulative number of people exiting during evacuation. Our results show that the inclusion of GA, NNs, and fuzzy attributes made the evacuation time of the agents closer to the real-time evacuation drills.     

Smile and the world will smile with you—The effects of a virtual agent‘s smile on users’ evaluation and behavior

Recent studies have demonstrated that people show social reactions when interacting with human-like virtual agents. For instance, human users behave in a socially desirable way, show increased cooperation or apply human-like communication. It has, however, so far not been tested whether users are prone to mimic the artificial agent’s behavior although this is a widely cited phenomenon of human–human communication that seems to be especially indicative of the sociality of the situation. We therefore conducted an experiment, in which we analyzed whether humans reciprocate an agent’s smile. In a between-subjects design, 104 participants conducted an 8-min small-talk conversation with an agent that either did not smile, showed occasional smiles, or displayed frequent smiles. Results show that although smiling did not have a distinct impact on the evaluation of the agent, the human interaction partners themselves smiled longer when the agent was smiling.     

Virtual team meetings: An analysis of communication and context

We report a simulation study of virtual team meetings. Participants role-played companies collaborating on a design problem while supported by a range of IT tools, such as videoconferencing and shared applications. Meetings were analysed to investigate how sharing computing facilities, operating the technology, and company status, influenced communications. Significantly more talk occurred in larger teams where participants shared I.T. facilities BUT this extra talk was restricted to talk within a single location. No extra talk was shared across the virtual team via the communications link. Where facilities were shared, technology controllers dominated cross-site talk. To encourage free communication across distributed virtual teams we recommend providing each participant with their own communications facility even if this is technologically less advanced than if technology support were shared.     

Modeling culture in intelligent virtual agents

This work addresses the challenge of creating virtual agents that are able to portray culturally appropriate behavior when interacting with other agents or humans. Because culture influences how people perceive their social reality it is important to have agent models that explicitly consider social elements, such as existing relational factors. We addressed this necessity by integrating culture into a novel model for simulating human social behavior. With this model, we operationalized a particular dimension of culture—individualism versus collectivism—within the context of an interactive narrative scenario that is part of an agent-based tool for intercultural training. Using this scenario we conducted a cross-cultural study in which participants from a collectivistic country (Portugal) were compared with participants from an individualistic country (the Netherlands) in the way they perceived and interacted with agents whose behavior was either individualistic or collectivistic, according to the configuration of the proposed model. In the obtained results, Portuguese subjects rated the collectivistic agents more positively than the Dutch but both countries had a similarly positive opinion about the individualistic agents. This experiment sheds new light on how people from different countries differ when assessing the social appropriateness of virtual agents, while also raising new research questions on this matter.     

Design of an emotional and social interaction paradigm for the animation of 3D characters: the case of a therapy for brain injured people (the mirror neuron paradigm)

We propose an emotional and social interaction paradigm for the behavioural animation of virtual characters. Our research focuses on the production of verbal and paraverbal interactions between a human and a virtual character in the context of virtual therapy. The aim of this project is to assess virtual therapies for the rehabilitation of people with brain injuries caused by cerebral vascular accidents. The therapeutic paradigm is based on the neuroscience concept of “mirror neurones” which emphasise the perceptual side in the process of recovering neural damage. In our paradigm, the patient interacts with a virtual therapist (embodied autonomous agent) that guides and encourages him in order to fulfil the drills. Furthermore and following the “mirror neurone paradigm”, the patient can only see his virtual hands (which are handicapped). The virtual platform provides the patient with a vision of his hands undertaking a movement that he cannot perform. Doing so, we expect that the perception of this virtual movement may improve the recuperation (mirror neurone paradigm). In this paper, we also introduce the notion of an “intelligent emotional character” to produce a sense of social as well as emotional immersion in order to improve the interaction between the patient and the virtual therapist. We discuss the role of emotional interaction in the context of virtual social interaction and in particular its reflexive dimension. Finally, we present an architecture for the animation of virtual characters based on a multidisciplinary approach to model the emotional and social interaction.     

See how they run: modeling evacuations in VR

A virtual reality application called Vegas lets users experiment in real time with evacuation scenarios. Colt Virtual Reality, Ltd., based in Hampshire, United Kingdom, developed Vegas (virtual egress analysis and simulation), which runs on a 486-based PC. Its designers say that other evacuation models lack the user-friendly visualization of Vegas, and they hope its graphic capabilities will make the data available and comprehensible to a wider audience. In particular, they hope it will allow people to see how quickly fire and smoke can spread, and how important fast and calm action can be in an emergency. Colt has used Vegas to predict egress times from an underground subway station and evacuation times from a cross-channel ferry, as well as from several other, more traditional, buildings     

An ACL for a Dynamic System of Agents

In this article we present the design of an ACL for a dynamic system of agents. The ACL includes a set of conversation performatives extended with operations to register, create, and terminate agents. The main design goal at the agent–level is to provide only knowledge–level primitives that are well integrated with the dynamic nature of the system. This goal has been achieved by defining an anonymous interaction protocol which enables agents to request and supply knowledge without considering symbol–level issues concerning management of agent names, routing, and agent reachability. This anonymous interaction protocol exploits a distributed facilitator schema which is hidden at the agent–level and provides mechanisms for registering capabilities of agents and delivering requests according to the competence of agents. We present a formal specification of the ACL and of the underlying architecture, exploiting an algebra of actors, and illustrate it with the help of a graphical notation. This approach provides the basis for discussing dynamic primitives in ACL and for studying properties of dynamic multi agent systems, for example concerning the behavior of agents and the correctness of their conversation policies.     

Animating synthetic dyadic conversations with variations based on context and agent attributes

Conversations between two people are ubiquitous in many inhabited contexts. The kinds of conversations that occur depend on several factors, including the time, the location of the participating agents, the spatial relationship between the agents, and the type of conversation in which they are engaged. The statistical distribution of dyadic conversations among a population of agents will therefore depend on these factors. In addition, the conversation types, flow, and duration will depend on agent attributes such as interpersonal relationships, emotional state, personal priorities, and socio‐cultural proxemics. We present a framework for distributing conversations among virtual embodied agents in a real‐time simulation. To avoid generating actual language dialogues, we express variations in the conversational flow by using behavior trees implementing a set of conversation archetypes. The flow of these behavior trees depends in part on the agents' attributes and progresses based on parametrically estimated transitional probabilities. With the participating agents' state, a ‘smart event’ model steers the interchange to different possible outcomes as it executes. Example behavior trees are developed for two conversation archetypes: buyer–seller negotiations and simple asking–answering; the model can be readily extended to others. Because the conversation archetype is known to participating agents, they can animate their gestures appropriate to their conversational state. The resulting animated conversations demonstrate reasonable variety and variability within the environmental context. Copyright © 2012 John Wiley & Sons, Ltd.     

Let's talk! Socially intelligent agents for language conversationtraining

This paper promotes socially intelligent animated agents for the pedagogical task of English conversation training for native speakers of Japanese. As a novel feature, social role awareness is introduced to animated conversational agents, that are by non-strong affective reasoners, but otherwise often lack the social competence observed in humans. In particular, humans may easily adjust their behavior depending on their respective role in a social setting, whereas their synthetic pendants tend to be driven mostly by emotions and personality. Our main contribution is the incorporation of a “social filter program” to mental models of animated agents. This program may qualify an agent's expression of its emotional state by the social contest, thereby enhancing the agent's believability as a conversational partner. Our implemented system is web-based and demonstrates socially aware animated agents in a virtual coffee shop environment. An experiment with our conversation system shows that users consider socially aware agents as more natural than agents that violate conventional practices     

CAIRO: a concurrent engineering meeting environment for virtual design teams

This paper presents the software architecture for a next generation concurrent engineering environment that helps geographically separated designers and engineers to collaborate effectively. The paper highlights research in computer-supported collaboration work (CSCW) based on various models of group interaction, social communication theory, negotiation theory and distributed artificial intelligence concepts. The paper describes CAIRO (Collaborative Agent Interaction and synchROnization) system, a distributed conferencing architecture for managing designers and engineers in a distributed design meeting. The CAIRO system allows designers and engineers to work together in virtual teams by supporting multi-media interactions over computer networks. CAIRO aids the concurrent engineering effort by relaxing the physical, temporal and organizational constraints experienced in traditional design meeting environments. CAIRO provides both media synchronization, i.e. ensuring that all information exchanged between users is synchronized, and agent synchronization, i.e. ensuring effective structuring and control of a distributed conference. This paper also details the prototype CAIRO system with a detailed example, illustrating its use in concurrent design settings.     

The value of learning talk: applying a novel dialogue scoring method to inform interaction design in an open-ended,embodied museum exhibit

Museum researchers have long acknowledged the importance of dialogue in informal learning, particularly for open-ended exploratory exhibits. Novel interaction techniques like full-body interaction are appealing for these exploratory exhibits, but designers have not had a metric for determining how their designs are supporting productive learning talk. Moreover, with the incorporation of digital technologies into museums, researchers and designers now have the opportunity for in situ A/B testing of multiple exhibit designs not previously possible with traditionally constructed exhibits, which once installed were difficult and expensive to iterate. Here we present a method called Scoring Qualitative Informal Learning Dialogue (SQuILD) for quantifying idiosyncratic social learning talk, in order to conduct in situ testing of group learning at interactive exhibits. We demonstrate how the method was applied to a 2 × 2 experiment varying the means of control (full-body vs. handheld tablet controller) and the distribution of control (single-user-input vs. multi-user-input) of an interactive data map exhibit. Though pilot testing in the lab predicted that full-body and multi-input designs would best support learning talk, analysis of dialogue from 119 groups’ interactions revealed surprising nuances in the affordances of each. Implications for embodied interaction design are discussed.     

Negotiated Collusion: Modeling Social Language and its Relationship Effects in Intelligent Agents

Building a collaborative trusting relationship with users is crucial in a wide range of applications, such as advice-giving or financial transactions, and some minimal degree of cooperativeness is required in all applications to even initiate and maintain an interaction with a user. Despite the importance of this aspect of human–human relationships, few intelligent systems have tried to build user models of trust, credibility, or other similar interpersonal variables, or to influence these variables during interaction with users. Humans use a variety of kinds of social language, including small talk, to establish collaborative trusting interpersonal relationships. We argue that such strategies can also be used by intelligent agents, and that embodied conversational agents are ideally suited for this task given the myriad multimodal cues available to them for managing conversation. In this article we describe a model of the relationship between social language and interpersonal relationships, a new kind of discourse planner that is capable of generating social language to achieve interpersonal goals, and an actual implementation in an embodied conversational agent. We discuss an evaluation of our system in which the use of social language was demonstrated to have a significant effect on users’ perceptions of the agent’s knowledgableness and ability to engage users, and on their trust, credibility, and how well they felt the system knew them, for users manifesting particular personality traits.This revised version was published online in July 2005 with corrections to the author name Bickmore.     

A model of agents (robots) command behavior: The cognitive approach

The paper suggests a mathematical model of agents’ cooperation in dynamics, which employs agents’ utility functions and cognitive dissonance of their relations. The model is based on the theories of social psychologists investigating the behavior of people in small social groups and explaining the principles of their functioning and stability. We illustrate the suggested model via simulation of virtual soccer game of agents (robots). The performed simulation allows to model diverse aspects of agents’ cooperation and selfish behavior.     

Multiagent-Based Multi-team Formation Control for Mobile Robots

In the field of formation control, researchers generally control multiple robots in only one team, and little research focuses on multi-team formation control. In this paper, we propose an architecture, called Virtual Operator MultiAgent System (VOMAS), to perform formation control for multiple teams of mobile robots with the capabilities and advantages of scalability and autonomy. VOMAS is a hybrid architecture with two main agents. The virtual operator agent handles high level missions and team control, and the robot agent deals with low level formation control. The virtual operator uses four basic services including join, remove, split, and merge requests to perform multi-team control. A new robot can be easily added to a team by cloning a new virtual operator to control it. The robot agent uses a simple formation representation method to show formation to a large number of robots, and it uses the concept of potential field and behavior-based control to perform kinematic control to keep formation both in holonomic and nonholonomic mobile robots. In addition, we also test the stability, robustness, and uncertainty in the simulation. This research was supported by the National Science Council under grant NSC 91-2213-E-194-003.     

The design of a JADE-based autonomous workflow management system for collaborative SoC design

Given a fast changing electronics goods marketplace, designers of integrated circuits and components need to be more competitive, efficient, flexible, and use collaborative workflow to reduce time-to-market and a project’s life cycle. In recent years, agent-based workflow management systems (WfMS) have been widely used to monitor and control business design processes. In this paper, intelligent agents are applied to the collaborative system-on-chip (SoC) design environment. The proposed JADE-based autonomous workflow management system (JAWMS) uses a workflow coordination mechanism and an agent integration mechanism to enable the analysis, management and interaction of automated design processes. The workflow coordination mechanism uses five domain specific agents to perform the workflow enactment services and a generic agent to control the system flow logic. The system kernel of JAWMS follows the specifications of the workflow reference model provided by the workflow management coalition (WfMC). The agent integration mechanism supports an agent to interact with other JADE-based agent platforms and to coordinate and monitor workflow coordination messages. All agents are written in the Java language using the JADE platform and work together to perform flexible, adaptive and dynamic design tasks in an autonomous and collaborative way. JAWMS facilitates SoC design and team interaction in a collaborative but distributed product development environment.     

Cooperating with life-like interface agents

As computer interfaces can display more life-like qualities such as speech output and personable characters or agents, it becomes important to understand and assess users’ interaction behavior within a social interaction framework rather than only a narrower machine interaction one. We studied how the appearance of a life-like interface agent influenced people’s interaction with it, using a social interaction framework of making and keeping promises to cooperate. Participants played a social dilemma game with a human confederate via realtime video conferencing or with one of three interface agents: a person-like interface agent, a dog-like interface agent, or a cartoon dog interface agent. Technology improvements from a previous version of the human-like interface led to increased cooperation with it; participants made and kept promises to cooperate with the person-like interface agent as much as with the confederate. Dog owners also made and kept promises to dog-like interface agents. General evaluations of likability and appealingness of the interface agent did not lead people to cooperate with it. Our findings demonstrate the importance of placing user interface studies within a social interaction framework as interfaces become more social.     

Generation of augmented video sequences combining behavioral animation and multi‐object tracking

In this paper we present a novel approach to generate augmented video sequences in real‐time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi‐object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. The resulting framework allows to generate video sequences involving behavior‐based virtual agents that react to real agent behavior and has applications in education, simulation, and in the game and movie industries. We show the performance of the proposed approach in an indoor and outdoor scenario simulating human and vehicle agents. Copyright © 2009 John Wiley & Sons, Ltd.     

Social decisions and fairness change when people’s interests are represented by autonomous agents

There has been growing interest on agents that represent people’s interests or act on their behalf such as automated negotiators, self-driving cars, or drones. Even though people will interact often with others via these agent representatives, little is known about whether people’s behavior changes when acting through these agents, when compared to direct interaction with others. Here we show that people’s decisions will change in important ways because of these agents; specifically, we showed that interacting via agents is likely to lead people to behave more fairly, when compared to direct interaction with others. We argue this occurs because programming an agent leads people to adopt a broader perspective, consider the other side’s position, and rely on social norms—such as fairness—to guide their decision making. To support this argument, we present four experiments: in Experiment 1 we show that people made fairer offers in the ultimatum and impunity games when interacting via agent representatives, when compared to direct interaction; in Experiment 2, participants were less likely to accept unfair offers in these games when agent representatives were involved; in Experiment 3, we show that the act of thinking about the decisions ahead of time—i.e., under the so-called “strategy method”—can also lead to increased fairness, even when no agents are involved; and, finally, in Experiment 4 we show that participants were less likely to reach an agreement with unfair counterparts in a negotiation setting. We discuss theoretical implications for our understanding of the nature of people’s social behavior with agent representatives, as well as practical implications for the design of agents that have the potential to increase fairness in society.     

人群应急疏散可视仿真研究进展和问题

人群应急疏散可视仿真是用智能体来模拟具有自主感知、情绪和行为能力的人群个体,并采用3维可视的方式来直观呈现人群应急疏散情景,可以为制定人群应急预案提供形象直观的分析方法。本文从人群仿真数据的来源、人群导航模型的构建、人群行为模型、人群情绪感染、人群渲染5个方面概述目前研究的进展,然后从仿真模型的可验证性、人群疏散导航模型的构建、人与环境的物理模型、动物逃生实验与仿真、疏散中的社会行为表现以及人群情绪的可视计算6个角度讨论需要进一步研究的问题。针对需要深入研究的问题,指出借助于紧急事件的视频监控分析和虚拟人群情景的用户调查,有助于完善人群仿真模型。结合物理模型,可以更准确地描述人群应急疏散场景。开展动物逃生实验分析,有助于完善人群运动导航算法。建立人群社会行为模型,可以更详细描述疏散中人群行为的多样性。构建基于多通道感知的人群情绪感染计算方法,可以详尽描述情绪感染的过程。人群应急疏散行为的可视仿真研究在城市的安全管理方面具有重要的应用前景,但其研究仍存在很多亟待解决的问题,综合地运用多学科知识,完善实验手段是进一步推动研究的关键所在。     

To Commit or Not to Commit: Modeling Agent Conversations for Action

Conversations are sequences of messages exchanged among interacting agents. For conversations to be meaningful, agents ought to follow commonly known specifications limiting the types of messages that can be exchanged at any point in the conversation. These specifications are usually implemented using conversation policies (which are rules of inference) or conversation protocols (which are predefined conversation templates). In this article we present a semantic model for specifying conversations using conversation policies. This model is based on the principles that the negotiation and uptake of shared social commitments entail the adoption of obligations to action, which indicate the actions that agents have agreed to perform. In the same way, obligations are retracted based on the negotiation to discharge their corresponding shared social commitments. Based on these principles, conversations are specified as interaction specifications that model the ideal sequencing of agent participations negotiating the execution of actions in a joint activity. These specifications not only specify the adoption and discharge of shared commitments and obligations during an activity, but also indicate the commitments and obligations that are required (as preconditions) or that outlive a joint activity (as postconditions). We model the Contract Net Protocol as an example of the specification of conversations in a joint activity.