Semiotic dynamics for embodied agents

Artificial intelligence explores the many different aspects of intelligence like a meandering stream carving out rivers, lakes, and deltas in an endless magnificent landscape. Each time new vistas on intelligence open up, we build new technologies to explore them and find new types of applications. In this article, the author briefly illustrate the current study of semiotic dynamics, the resulting technologies, and the field's impact on current and future intelligent systems applications.     

Social evaluations of embodied agents and avatars

The purpose of this study was to examine social evaluations (i.e., perceptions of empathy and positivity) following peoples’ interactions with digital human representations. Female research participants engaged in a 3-min interaction while immersed in a 3-D immersive virtual environment with a “peer counselor.” Participants were led to believe that the peer counselor was either an embodied agent (i.e., computer algorithm) or an avatar (i.e., another person). During the interaction, the peer counselor either smiled or not. As predicted, a digitally-rendered smile was found to affect participants’ social evaluations. However, these effects were moderated by participants’ beliefs about their interaction partner. Specifically, smiles enhanced social evaluations of embodied agents but degraded them for avatars. Although these results are consistent with other findings concerning the communicative realism of embodied agents and avatars they uniquely demonstrate that people’s beliefs alone, rather than actual differences in virtual representations, can impact social evaluations.     

Multimodal behavior realization for embodied conversational agents

Applications with intelligent conversational virtual humans, called Embodied Conversational Agents (ECAs), seek to bring human-like abilities into machines and establish natural human-computer interaction. In this paper we discuss realization of ECA multimodal behaviors which include speech and nonverbal behaviors. We devise RealActor, an open-source, multi-platform animation system for real-time multimodal behavior realization for ECAs. The system employs a novel solution for synchronizing gestures and speech using neural networks. It also employs an adaptive face animation model based on Facial Action Coding System (FACS) to synthesize face expressions. Our aim is to provide a generic animation system which can help researchers create believable and expressive ECAs.     

Evaluating the effects of behavioral realism in embodied agents

Designers of embodied agents constantly strive to create agents that appear more human-like, with the belief that increasing the human-likeness of agents will improve users’ interactions with agents. While designers have focused on visual realism, less attention has been paid to the effects of agents’ behavioral realism on users’ responses. This paper presents an empirical study that compared three theories of agent realism: Realism Maximization Theory, Uncanny Valley Theory, and Consistency Theory. Results of this study showed that people responded best to an embodied agent when it demonstrated moderately realistic, inconsistent behavior. These results support Uncanny Valley Theory and demonstrate the powerful influence of agent behavior on users’ responses.     

Specifying and animating facial signals for discourse in embodied conversational agents

People highlight the intended interpretation of their utterances within a larger discourse by a diverse set of non‐verbal signals. These signals represent a key challenge for animated conversational agents because they are pervasive, variable, and need to be coordinated judiciously in an effective contribution to conversation. In this paper, we describe a freely available cross‐platform real‐time facial animation system, RUTH , that animates such high‐level signals in synchrony with speech and lip movements. RUTH adopts an open, layered architecture in which fine‐grained features of the animation can be derived by rule from inferred linguistic structure, allowing us to use RUTH , in conjunction with annotation of observed discourse, to investigate the meaningful high‐level elements of conversational facial movement for American English speakers. Copyright © 2004 John Wiley & Sons, Ltd.     

A data-driven passing interaction model for embodied basketball agents

Human beings have an ability to transition smoothly between individual and collaborative activities and to recognize these types of activity in other humans. Our long-term goal is to devise an agent which can function intelligently in an environment with frequent switching between individual and collaborative tasks. A basketball scenario is such an environment, however there currently do not exist suitable interactive agents for this domain. In this paper we take a step towards intelligent basketball agents by contributing a data-driven generalized model of passing interactions. We first collect data on human-human interaction in virtual basketball to discover patterns of behavior surrounding passing interactions. Through these patterns we produce a model of rotation behavior before and after passes are executed. We then implement this model into an actual basketball agent and then conduct an experiment with a human-agent team. Results show that the agent using the model can at least communicate better than a task-competent agent with limited communication, with participants rating the agent as being able to recognize and express its intention. In addition we analyze passing interactions using Herbert Clark’s joint activity theory and propose that the concepts, while completely theoretical, should be considered as a basis for agent design.     

The affective outcomes of using influence tactics in embodied conversational agents

In this study, we highlight the theoretical underpinnings of human impression management tactics and link them to current research in embodied conversational agents. Specifically, we incorporated impression management behaviors into an embodied conversational agent in order to show that different influence strategies affect user perceptions, and how those perceptions might be moderated by user gender. We programmed the agent to use two human impression management techniques (ingratiation and self-promotion) and had the agent interact with 88 users. After the interaction, users reported their perceptions of the system’s power, trustworthiness, expertise, and attractiveness. The impression management techniques altered users’ perceptions and these perceptions were moderated by gender differences.     

A comparison study of 12 paradigms for developing embodied agents

We report on a study in which 12 different paradigms were used to implement agents acting in an environment which borrows elements from artificial life and multi‐player strategy games. In choosing the paradigms we strived to maintain a balance between high‐level, logic‐based approaches and low‐level, physics‐oriented models; between imperative programming, declarative approaches and ‘learning from basics’; between anthropomorphic or biologically inspired models on one hand and pragmatic, performance‐oriented approaches on the other. We have found that the choice of the paradigm determines the software development process and requires a different set of skills from the developers. In terms of raw performance, we found that the best performing paradigms were those which (a) allowed the knowledge of human experts to be explicitly transferred to the agent and (b) allowed the integration of well‐known, high‐performance algorithms. We have found that maintaining a commitment to the chosen paradigm can be difficult; there is a strong temptation to offer shallow fixes to perceived performance problems through a ‘flight into heuristics’. Our experience is that a development process without the discipline enforced by a central paradigm leads to agents which are a random collection of heuristics whose interactions are not clearly understood. Although far from providing a definitive verdict on the benefits of the different paradigms, our study provided a good insight into what kind of conceptual, technical or organizational problems would a development team face depending on their choice of agent paradigm. Copyright © 2007 John Wiley & Sons, Ltd.     

Modeling and evaluating IPTV applications in WiMAX networks

Internet Protocol-based Television (IPTV) is a digital television service which delivers television content via an IP network. The rapid growth of wireless network technology in recent years has changed, the way people access the Internet. Adding mobility to IPTV can create a truly compelling ubiquitous service which spans different network domains and varied IP-enabled terminals and devices, such as set-top boxes, PCs and cell phones. However, extending IPTV service to wireless networks requires overcoming bandwidth bottlenecks and high packet loss rates. Following the IEEE 802.16 standard, worldwide interoperability for microwave access (WiMAX) features high data rates and large service coverage, offering a wireless broadband solution for IPTV services. While previous research has focused on creating a broadband IPTV service few studies have practically evaluated IPTV applications in a wireless broadband network environment. In this paper, we model and evaluate a common constant bit rate (CBR)¹ based IPTV application and an IPTV live streaming (PPStreaming)² application while retrieving IPTV content via a WiMAX network. We also use the NS2 simulation tool to evaluate the performance of these two IPTV applications. The evaluation metrics include latency, packet loss, data rate and throughput statistics when the two IPTV applications are run in the WiMAX network. ¹The simplest IPTV solution is to convey video content by CBR. IPTV operators and content delivery networks relay CBR streaming content to control the demand for network capacity. Broadcasters prefer CBR video as it conserves bandwidth resources, but CBR delivery can degrade video quality result in higher overall demand on network capacity. ²PPStreaming (also referred to as P2P streaming Internet TV) is a network for live media streaming. In principle it’s similar to BitTorrent (BT) in that it provides stable and smooth broadcast of TV programs to broadband users. Unlike traditional streaming media, PPStreaming adopts P2P-streaming technology and supports full-scale visits with tens of thousands of simultaneous users. Its client software can be used in the browser or as a standalone executable.     

Modeling social inference in virtual agents

Social judgment is a social inference process whereby an agent singles out individuals to blame or credit for multi-agent activities. Such inferences are a key aspect of social intelligence that underlie social planning, social learning, natural language pragmatics and computational models of emotion. With the advance of multi-agent interactive systems and the need of designing socially aware systems and interfaces to interact with people, it is increasingly important to model this human-centric form of social inference. Based on psychological attribution theory, this paper presents a general computational framework to automate social inference based on an agent’s causal knowledge and observations of interaction.     

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.     

Modeling and evaluating of typical advanced peer-to-peer botnet

In this paper, we present a general model for an advanced peer-to-peer (P2P) botnet, in which the performance of the botnet can be systematically studied. From the model, we can derive five performance metrics to describe the robustness, security and efficiency of the botnet. Additionally, we analyze the relationship between the performance metrics and the model feature metrics of the botnet, and it is helpful to study the botnet under different model feature metrics. Furthermore, the proposed model can be easily applied to other types of botnets. Finally, taking the robustness and security into consideration, an optimization scheme for designing an optimal P2P botnet is proposed.     

Modeling and evaluating beat gestures for social robots

Multimedia Tools and Applications - Natural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a more comfortable interaction in people. With this aim in mind, we...     

Modeling adaptive empathy based on neutral assessment: a way to enhance the prosocial behaviors of socialized agents under the premise of self-security

Applied Intelligence - Ethical concerns over artificial intelligence (AI) have recently drawn extensive interest in both academia and industry. According to behavioral economics and...     

利用Stencil建模及评估Intel IMCI vgather指令

Intel Xeon Phi协处理器的指令集IMCI引入了硬件实现的vgather指令,旨在帮助512位SIMD寄存器访问非连续内存地址上的数据。然而实验结果显示,vgather很有可能成为应用在Xeon Phi协处理器上关键的性能瓶颈之一。基于以上结论,针对vgather的性能建模可以帮助用户深入地掌握和理解Xeon Phi协处理器的性能特性。在实验方法上,本文方法与现存的通过程序段内嵌入汇编代码进行数据统计不同,使用PAPI等性能分析工具直接收集硬件计数器的统计结果,作为模型的实验数据。本文的性能模型基于AGI事件次数和根据VPU_DATA_READ次数估算得出的vgather所导致的平均延迟构建而成。该模型能够对Xeon Phi应用代码中由vgather所导致的总延迟进行预测。最终,为了验证模型预测的准确性,将该模型应用在三维7点stencil应用代码上,预测结果显示,vgather耗时占计算总耗时的约40%。再将该结果与利用intrinsics指令去除vgather后的计算耗时进行了对比验证,结果显示模型预测准确。基于上述结论,采用硬件计数器的统计结果在Xeon Phi协处理器上针对vgather构建了性能模型。同时,通过与其他平台的vgather对比,认为该模型也可以应用在同样具备vgather的Intel CPU处理器平台上。     

Modeling and evaluating information leakage caused by inferences in supply chains

While information sharing can benefit supply chains significantly, it may also have an adverse effect, namely, information leakage. A limitation common to many existing solutions for preventing information leakage in supply chains is that they rely, either implicitly or explicitly, upon two unrealistic assumptions. First, what information is confidential is well known. Second, confidential information will not be revealed, if only it is not shared, regardless of how much other information is being shared. As we shall show in this paper, those assumptions are not always true due to potential information leakage caused by inferences. Specifically, we propose a conceptual model of such information leakage. The model will enable companies in a supply chain to better understand how their confidential information may be leaked through inferences. On the basis of the proposed conceptual model, we then devise a quantitative approach to evaluating the risk of information leakage caused by inferences when a given amount of information is shared. The quantitative approach will allow companies in a supply chain to measure and consequently mitigate the risk of information leakage. Finally, we discuss a case study to illustrate how the proposed approaches work in practice.