When products receive reviews across platforms: Studying the platform concentration of electronic word-of-mouth

A product can receive Electronic Word-of-Mouth (eWOM), e.g., user reviews, at both retail and review platforms, with considerable variance in volume and valence. We define such eWOM variation across platforms as the platform concentration of eWOM. A lower platform concentration is measured by a higher level of volume equality and valence equality, i.e., a more comparable number of user reviews and more consistent average ratings among multiple platforms, respectively. Results from multiple models over software data from retail and review platforms shows that volume equality and valence equality positively interact to affect online users’ product adoption decisions.     

Designing multi-agent unit tests using systematic test design patterns-(extended version)

Software agents are the basic building blocks in many software systems especially those based on artificial intelligence methods, e.g., reinforcement learning based multi-agent systems (MASs). However, testing software agents is considered a challenging problem. This is due to the special characteristics of agents which include its autonomy, distributed nature, intelligence, and heterogeneous communication protocols. Following the test-driven development (TDD) paradigm, we present a framework that allows MAS developers to write test scenarios that test each agent individually. The framework relies on the concepts of building mock agents and testing common agent interaction design patterns. We analyze the most common agent interaction patterns including pair and mediation patterns in order to provide stereotype implementation for their corresponding test cases. These implementations serve as test building blocks and are provided as a set of ready-for-reuse components in our repository. This way, the developer can concentrate on testing the business logic itself and spare him/her the burden of implementing tests for the underlying agent interaction patterns. Our framework is based on standard components such as the JADE agent platform, the JUnit framework, and the eclipse plug-in architecture. In this paper, we present in details the design and function of the framework. We demonstrate how we can use the proposed framework to define more stereotypes in the code repository and provide a detailed analysis of the code coverage for our designed stereotype test code implementations.     

CILIOS: Connectionist inductive learning and inter-ontology similarities for recommending information agents

For a software information agent, operating on behalf of a human owner and belonging to a community of agents, the choice of communicating or not with another agent becomes a decision to take, since communication generally implies a cost. Since these agents often operate as recommender systems, on the basis of dynamic recognition of their human owners’ behaviour and by generally using hybrid machine learning techniques, three main necessities arise in their design, namely (i) providing the agent with an internal representation of both interests and behaviour of its owner, usually called ontology; (ii) detecting inter-ontology properties that can help an agent to choose the most promising agents to be contacted for knowledge-sharing purposes; (iii) semi-automatically constructing the agent ontology, by simply observing the behaviour of the user supported by the agent, leaving to the user only the task of defining concepts and categories of interest. We present a complete MAS architecture, called connectionist learning and inter-ontology similarities (CILIOS), for supporting agent mutual monitoring, trying to cover all the issues above. CILIOS exploits an ontology model able to represent concepts, concept collections, functions and causal implications among events in a multi-agent environment; moreover, it uses a mechanism capable of inducing logical rules representing agent behaviour in the ontology by means of a connectionist ontology representation, based on neural-symbolic networks, i.e., networks whose input and output nodes are associated with logic variables.     

Evaluating the security of mobile agent platforms

Mobility of software agents requires additional security measures. While the theoretical aspects of mobile agent security have been widely studied, there are few studies about the security levels of current agent platforms. In this paper, test cases are proposed to assess agent platform security. These tests focus on malicious agents trying to attack other agents or the agency. Currently, they have been carried out for two agent platforms: JADE and SeMoA. These tests show which of the known theoretical security problems are relevant in practice. Furthermore, they reveal how these problems are addressed by the respective platform and what security flaws are present.     

Legal complicance by design: technical solutions for future distributed electronic markets

A novel challenge for Internet-based electronic market platforms constitutes trading of short-lived or non-material goods (e.g., electrical power, bandwidth-on- demand). In such a scenario, distributed market platforms are superior to centralized market platforms in many respects, e.g., because of lower transaction costs, more flexible options for contract negotiations, scalability, and robustness. However, they lack legal certainty since they are not operated by a trusted third party. This paper discuses how the SESAM framework for distributed electronic markets provides legal certainty conforming to European regulations based on three building blocks: First, it models juristic expertise as a formal workflow. Second, it includes a legal advisor consulting the users that are often legal laities. Third, it provides provableness and verifiability. Besides other mechanisms, the last building block comprises a novel solution for adducing the reception of electronic documents in a distributed setting. The real life example of trading energy on an electronic market platform is used to illustrate the interworking of all building blocks.     

Analysis and improvement of business process models using spreadsheets

Software in general is thoroughly analyzed before it is released to its users. Business processes often are not – at least not as thoroughly as it could be – before they are released to their users, e.g., employees or software agents. This paper ascribes this practice to the lack of suitable instruments for business process analysts, who design the processes, and aims to provide them with the necessary instruments to allow them to also analyze their processes. We use the spreadsheet paradigm to represent business process analysis tasks, such as writing metrics and assertions, running performance analysis and verification tasks, and reporting on the outcomes, and implement a spreadsheet-based tool for business process analysis. The results of two independent user studies demonstrate the viability of the approach.     

面向Agent软件工程在企业素质诊断系统中的应用

在企业素质诊断系统的开发中引入AOSE,分析了AOSE方法在实际工作中的不足.在开发过程中以软件智能体系统工程方法学(MESSAGE)建模语言为一致性规则,采用愿望-意图-信念(D-I-B)次序的建模方法进行Agent设计.以JADE和Jadex为开发平台,给出了BDI Agent等关键技术的实现,总结出一个完整和系统的面向Agent软件开发过程.     

The role of information structures in game-theoretic multi-agent learning

Multi-agent learning (MAL) studies how agents learn to behave optimally and adaptively from their experience when interacting with other agents in dynamic environments. The outcome of a MAL process is jointly determined by all agents’ decision-making. Hence, each agent needs to think strategically about others’ sequential moves, when planning future actions. The strategic interactions among agents makes MAL go beyond the direct extension of single-agent learning to multiple agents. With the strategic thinking, each agent aims to build a subjective model of others decision-making using its observations. Such modeling is directly influenced by agents’ perception during the learning process, which is called the information structure of the agent’s learning. As it determines the input to MAL processes, information structures play a significant role in the learning mechanisms of the agents. This review creates a taxonomy of MAL and establishes a unified and systematic way to understand MAL from the perspective of information structures. We define three fundamental components of MAL: the information structure (i.e., what the agent can observe), the belief generation (i.e., how the agent forms a belief about others based on the observations), as well as the policy generation (i.e., how the agent generates its policy based on its belief). In addition, this taxonomy enables the classification of a wide range of state-of-the-art algorithms into four categories based on the belief-generation mechanisms of the opponents, including stationary, conjectured, calibrated, and sophisticated opponents. We introduce Value of Information (VoI) as a metric to quantify the impact of different information structures on MAL. Finally, we discuss the strengths and limitations of algorithms from different categories and point to promising avenues of future research.     

如何防止移动代理和代理平台之间的相互攻击

移动代理在实际应用中存在4种安全问题，即代理平台对代理平台的攻击、移动代理对代理平台的攻击、移动代理对移动代理的攻击和代理平台对移动代理的攻击。主要关注移动代理对代理平台的攻击和代理平台对移动代理的攻击及其解决方法。     

Protecting mobile agents from external replay attacks

This paper presents a protocol for the protection of mobile agents against external replay attacks. This kind of attacks are performed by malicious platforms when dispatching an agent multiple times to a remote host, thus making it reexecute part of its itinerary. Current proposals aiming to address this problem are based on storing agent identifiers, or trip markers, inside agent platforms, so that future reexecutions can be detected and prevented. The problem of these solutions is that they do not allow the agent to perform legal migrations to the same platform several times. The aim of this paper is to address these issues by presenting a novel solution based on authorisation entities, which allow the agent to be reexecuted on the same platform a number of times determined at runtime. The proposed protocol is secure under the assumption that authorisation entities are trusted.     

A legal analysis of human and electronic agents

Currently, electronic agents are being designed and implemented that, unprecedentedly, will be capable of performing legally binding actions. These advances necessitate a thorough treatment of their legal consequences. In our paper, we first demonstrate that electronic agents behave structurally similar to human agents. Then we study how declarations of intention stated by an electronic agent are related to ordinary declarations of intention given by natural persons or legal entities, and also how the actions of electronic agents in this respect have to be classified under German law. We discuss four different approaches of classifying agent declarations. As one of these, we propose the concept of an electronic person (i.e., agents with limited liability), enrolment of agents into an agent register, and agent liability funds as means to serve the needs of all contracting parties.     

Bargaining on an Internet Agent-based Market: Behavioral vs. Optimizing Agents

In this paper, we analyze an Internet agent-based market where non-cooperative agents using behavioral rules negotiate the price of a given product in a bilateral and sequential manner. In this setting, we study the optimal decision-making process of a buying agent that enters the market. Our approach is based on Negotiation Analysis (Raiffa, 1982; Sebenuis, 1992) and we consider that the optimizing buying agent maximizes her discounted expected utility using subjective probabilities. The optimal decision-making process of the buying agent is treated as a stochastic control problem that can be solved by dynamic programming. Three types of behavioral agents are studied, namely conceder agents, boulware agents and imitative agents. A set of simulations is undertaken in order to predict the average outcome in a negotiation process for different parameters of the optimizing buying agent and for the three possible selling agents' behaviors. Finally, we compare the performance of the optimizing agent with that of behavioral buying agents.     

Preliminary design and manufacturing planning integration using web-based intelligent agents

Software agents have been increasingly used in the product and process development in industry over the past years due to the rapid evolvement of the Internet technology. This paper describes agents for the integration of conceptual design and process planning. Agents provide mechanisms to interact with each other. This mechanism is important since both of those processes involve negotiations for optimization. A set of design and planning software agents has been developed. These agents are used in a computer-based collaborative environment, called a multi-agent platform. The main purpose of developing such a platform is to support product preliminary design, optimize product form and structure, and reduce the manufacturing cost in the early design stage. The agents on the platform have access to a knowledge base that contains design and planning rules. These rules are derived from an analysis of design factors that influence process and resource planning, such as product material, form, shape complexity, features, dimension, tolerance, surface condition, production volume, and production rate. These rules are used by process planning agents to provide process planners with information regarding selecting preliminary manufacturing processes, determining manufacturing resources, and constructing feedback information to product designers. Additionally, the agents communicate with WEB servers, and they are accessible by users through Internet browsers. During performing design and planning tasks, agents access the data pertinent to design and manufacturing processes by the programming interfaces of existing computer-aided design (CAD) and manufacturing system. The agents are supported by a developed prototype agent platform. The agents and the platform enable the information exchange among agents, based on a previously developed integrated design and manufacturing process object model.     

Deterministic Rendezvous of Asynchronous Bounded-Memory Agents in Polygonal Terrains

Two mobile agents, modeled as points starting at different locations of an unknown terrain, have to meet. The terrain is a polygon with polygonal holes. We consider two versions of this rendezvous problem: exact RV, when the points representing the agents have to coincide at some time, and ε-RV, when these points have to get at distance less than ε in the terrain. In any terrain, each agent chooses its trajectory, but the movements of the agent on this trajectory are controlled by an adversary that may, e.g., speed up or slow down the agent. Agents have bounded memory: their computational power is that of finite state machines. Our aim is to compare the feasibility of exact and of ε-RV when agents are anonymous vs. when they are labeled. We show classes of polygonal terrains which distinguish all the studied scenarios from the point of view of feasibility of rendezvous. The features which influence the feasibility of rendezvous include symmetries present in the terrains, boundedness of their diameter, and the number of vertices of polygons in the terrains.     

Anonymity and software agents: An interdisciplinary challenge

Software agents that play a role in E-commerce and E-government applications involving the Internet often contain information about the identity of their human user such as credit cards and bank accounts. This paper discusses whether this is necessary: whether human users and software agents are allowed to be anonymous under the relevant legal regimes and whether an adequate interaction and balance between law and anonymity can be realised from both the perspective of Computer Systems and the perspective of Law.This paper is an extended and fully revised version of Brazier, Kubbe, Oskamp and Wijngaards (2002) and Brazier, Oskamp, Prins, Schellekens and Wijngaards (2003).     

Responsible agent behavior: a distributed computing perspective

Software agents that are autonomous, communicative, and possibly intelligent processes raise new questions for developers of distributed systems. Specifically, what is responsible agent behavior, and who, as the owner, is legally responsible for it? The answers involve an understanding of human-agent interaction, agent-oriented middleware, and social behavior. Some software agents will have a sufficiently large number of internal states to be capable of seemingly intelligent behavior. Hence, an agent's future external behavior cannot be guaranteed on the basis of its past behavior, even if that behavior has been monitored over time. Complete compliance tests of intelligent agents, therefore, may not be achievable because of the (possibly) large number of internal states. Thus, the best we can say is that an agent has not exhibited noncompliant behavior yet. Communication between agents implies a contract between owners, and the complexity of agents implies possibly unpredictable behavior. Therefore, an appropriate legal framework is required to underwrite the consequences of communicative actions and to provide safeguards against unlawful activities. The legal implications of agent technology require new ways of thinking about working with an agent, new requirements for agent-oriented middleware, and additional types of social behavior to be considered when designing a multiagent system     

Prominence convergence in the collective synchronization of situated multi-agents

In previous work on collective synchronization of multi-agents, they always follow the assumptions that the synchronization is flat where all agents have the same synchronization capacity and the final synchronization result always converges on a common average strategy. However, in many circumstances the above assumption does not match the peculiarities of real multi-agent societies where each agent plays a different role in the synchronization. To make up the restrictions of related work, this paper presents a non-flat synchronization model where the synchronization capacity of each agent is different regarding its social rank and strategy dominance. In the presented model, all agents are situated in a synchronization field where each agent can sense the collective synchronization forces from other agents; if some agents are more prominent than other ordinary agents (e.g., they have the dominance of social ranks or behavior strategies), they will have strong synchronization capacities in the field; and finally the collective synchronization results may incline to converge at such prominent agents' strategies, which is called prominence convergence in collective synchronization and can be proved by our theoretical analyses and experimental results.     

基于分布式可信度量的移动代理安全应用模型研究

本文主要讨论了可信计算平台上的移动代理安全方案。利用可信计算平台提供的可信度量策略与信任链机制,构建基于可信度量的移动代理安全体系结构。进一步地,在此类平台所构成的移动代理分布式计算环境中,建立了移动代理平台间基于可信度量的信任关系数学模型,并进行了数值模拟与测试验证。     

Trust and persistence [software agents]

We rely on computers to control our power plants and water supplies, our automobiles and transportation systems, and soon our economic and political systems. Increasingly, software agents are enmeshed in these systems, serving as the glue that connects distributed components. Clearly, we need mechanisms to determine whether these agents are trustworthy. What do we need to establish trust? Agents are often characterized by features such as autonomy, sociability, proactiveness, and persistent identity. This latter feature is key in determining trust. When agents operate over an extended period, they can earn a reputation for competence, timeliness, ease of use, and trustworthiness, which is something ephemeral agents cannot do. Along with persistence, we need a reliable way to identify an agent and ensure that its true identity is not concealed. How can we assess an agent's trustworthiness? As with other aspects of agents and multiagent systems, we can take our cue from the human domain. Our reputations for trustworthiness are determined and maintained by the people we deal with. Analogously, a software agent's reputation will reside within the other agents with whom it interacts. For some agent interactions, such as those involving commerce, agents will simply inherit the reputation of their human owner, sharing, for example, their owner's credit rating and financial capability. For other types of interactions, such as those involving information gathering, an agent will determine its own reputation through its efforts at gathering and distilling information. An agent with a reputation for conducting thorough searches will be trusted by other agents wishing to use its Web search results     

On scheduling dag s for volatile computing platforms: Area-maximizing schedules

Many modern computing platforms—notably clouds and desktop grids—exhibit dynamic heterogeneity: the availability and computing power of their constituent resources can change unexpectedly and dynamically, even in the midst of a computation. We introduce a new quality metric, area, for schedules that execute computations having interdependent constituent chores (jobs, tasks, etc.) on such platforms. Area measures the average number of tasks that a schedule renders eligible for execution at each step of a computation. Even though the definition of area does not mention and properties of host platforms (such as volatility), intuition suggests that rendering tasks eligible at a faster rate will have a benign impact on the performance of volatile platforms—and we report on simulation experiments that support this intuition. We derive the basic properties of the area metric and show how to efficiently craft area-maximizing (A-M) schedules for several classes of significant computations. Simulations that compare A-M scheduling against heuristics ranging from lightweight ones (e.g., FIFO) to computationally intensive ones suggest that A-M schedules complete computations on volatile heterogeneous platforms faster than their competition, by percentages that vary with computation structure and platform behavior—but are often in the double digits.