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With the advancement of artificial intelligence technologies, mobile agents are becoming more commonly used in a variety of industries that require high reliability from their control systems. In an uncertain environment, if the mobile agent control system's state transition includes only one plan, the system will enter the fault state immediately after the plan fails. Therefore, multiple alternative plans can be provided during the system design process to improve system reliability. First, this paper studies and describes the factors associated with the proposed multiple alternative plans, namely the success rate and plan implementation cost. Second, a Policy Generation Algorithm for identifying an appropriate execution sequence of those alternative plans is proposed. Furthermore, we propose a formal method-based pipeline framework for verifying the reliability of a mobile agent control system equipped with multiple alternative plans: we invoke the probabilistic model checking technique to create a Discrete-Time Markov Chain formal model of the mobile agent control system, convert the required properties into Probabilistic Computation Tree Logic formulae, and verify the model using the advanced probabilistic model checker PRISM. A case study is provided to demonstrate the applicability of the suggested methodological framework. The experimental results demonstrate that the proposed mobile agent control system with multiple alternative plans can improve system reliability while also meeting the least expected operational cost under the alternative plan set. [ABSTRACT FROM AUTHOR]

Much research in artificial intelligence is concerned with the development of autonomous agents that can interact effectively with other agents. An important aspect of such agents is the ability to reason about the behaviours of other agents, by constructing models which make predictions about various properties of interest (such as actions, goals, beliefs) of the modelled agents. A variety of modelling approaches now exist which vary widely in their methodology and underlying assumptions, catering to the needs of the different sub-communities within which they were developed and reflecting the different practical uses for which they are intended. The purpose of the present article is to provide a comprehensive survey of the salient modelling methods which can be found in the literature. The article concludes with a discussion of open problems which may form the basis for fruitful future research. [ABSTRACT FROM AUTHOR]

In the business process of reengineering, one of the main problems consists in the organizational reintegration of the employee. New instruments for the automatic identification of stakeholders among existing staff evaluation are needed. It is difficult to identify a stakeholder, especially if we refer to science stakeholders, and the proper evaluation of a researcher's value and position at international level is needed. There are large contradictions concerning the validity of various types of indexing services and other techniques used to classify the researchers. This paper proposes the use of corporate Human Resource Management (HRM) specific instruments when it comes to the researcher as informational stakeholder identification. The main idea behind the method is to use some form of information retrieval techniques over a set of research papers which contain, mostly, the same key words and to extract the hierarchy of the researchers involved/referenced over that set. A distributed approach was used due to its inherent scalability. The use of an inference engine was also deemed necessary due to the complexity of the problem. The system may be used in the automatic assessment of research performance in public or private institutions. It can be easily modified to support complex sets of rules depending on each user's needs in personnel evaluation. The main research field of this papers concerns distributed artificial intelligence. [ABSTRACT FROM AUTHOR]

The development of ubiquitous and pervasive computing systems requires new approaches and paradigms. Mobile agent based approaches have received a great attention for developing distributed applications. Agents are programs that can migrate from a machine to another in a network and perform tasks on distant machines. However, it is difficult to estimate a priori the appropriate number of agents allowed to be spawned in the network without any global information or controller. Indeed, increasing agent population size, with cloning operation, will increase resource demands in the network, which would indirectly affect the network performance. This paper focuses on the problem of dynamic regulation of mobile agent population size in a distributed system and proposes an approach that takes inspiration from the immune system concepts. Simulations have been conducted and results are reported to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

A review of popular technology adoption models identified several factors that are likely to influence Voice Activated Personal Assistant (VAPA) use in public spaces. To inform design decisions of how to make the private use of the VAPA in public spaces more acceptable from the users’ point of view, an online survey was conducted to investigate the likelihood of usage of the smartphone VAPA such as Apple’s Siri (compared to the usage of smartphone keyboard) as a function of location (private vs. public) and type of information (private vs. nonprivate). Responses from participants showed that users were more cautious of transmitting private than nonprivate information. This effect of type of information was amplified in the social context of public locations and when using conspicuous methods of information input such as the VAPA. Participants also preferred using the VAPA in private locations and showed no preference of location for keyboard entries. Correlations between likelihood of usage of VAPA and the social acceptability ratings were positive and predicted similar patterns of smartphone usage. [ABSTRACT FROM PUBLISHER]

In this paper we consider a multi agent planning problem where given a set of plans of the individual agents that may lead to conflict during execution, the task is to find a conflict-free plan for the agents. For this we give a formal model of the multi agent planning problem (MAPP) and give a description of the multi agent path planning. We demonstrate this technique in a grid world domain. The experimental results show promise for our method. [ABSTRACT FROM AUTHOR]

Abstract: This paper advocates the use of multi-agent systems in the freight forwarding industry. We propose an intelligent mobile agent system to cope with a dynamic freight forwarding environment where up-to-date information is crucial but time-consuming to obtain. A key component of our system is an agent argumentation mechanism that allows decision support agents to discuss, argue, and come to a compromise in order to derive well-explained freight planning solutions. A number of artificial intelligence mechanisms are implemented, namely: (1) a mobile-agent-based automated information gathering mechanism, where designated mobile agents access various websites automatically to gather information (e.g., weather conditions on a candidate route) critical for cargo consolidation and route planning, (2) a fuzzy logics engine for risk evaluation, and (3) a simulated annealing engine for optimizing cargo consolidation. A system prototype is developed and the feasibility of our approach is demonstrated in a case study. A series of experiments are also conducted to evaluate the system’s performance. [Copyright &y& Elsevier]

Abstract: An emerging technology for systems to communicate efficiently in the distributed environment is the mobile agent. The features of the mobile agent are too big when compared with the static agent and conventional communication system. However, the security issues of the mobile agent and mobile agent platform lags its usage. Even though the protection models are available for the mobile agent environment, the vulnerabilities still exist or the models need more computational time. To mitigate these issues related with the agent platform, this paper proposed an artificial immune system (AIS) based model. The proposed model will give the separation of duties and clones to handle multiple foreign agents simultaneously to achieve the computational efficiency. The experimental results and the constructed results from the experimental results have proved that this proposed model will consume less computational time when compared with the existing models. It will detect the malicious agent by extracting and matching the patterns with the available malicious patterns and also it can identify the new malicious patterns through monitoring the agent process. [Copyright &y& Elsevier]

Abstract: Many difficult problem solving require computational intelligence. One of the major directions in artificial intelligence consists in the development of efficient computational intelligence algorithms, like: evolutionary algorithms, and neural networks. Systems, that operate in isolation or cooperate with each other, like mobile robots could use computational intelligence algorithms for different problems/tasks solving, however in their behavior could emerge an intelligence called system''s intelligence, intelligence of a system. The traveling salesman problem TSP has a large application area. It is a well-known business problem. Maximum benefits TSP, price collecting TSP have a large number of economic applications. TSP is also used in the transport logic Raja, 2012. It also has a wide range of applicability in the mobile robotic agent path planning optimization. In this paper a mobile robotic agent''s path planning will be discussed, using unsupervised neural networks for the TSP solving, and from the TSP results the finding of a closely optimal path between two points in the agent''s working area. In the paper a modification of the criteria function of the winner neuron selection will also be presented. At the end of the paper measurement results will be presented. [Copyright &y& Elsevier]

In the age of Business-to-Business (B2B) collaboration, ensuring reliability of workflows underlying inter-organizational business processes is of significant importance. There are, however, quite a few challenges towards achieving seamless operation. Such challenges arise from heterogeneity in infrastructure and coordination mechanism at participant organizations, as well as time and cost associated with recovery from failure. Our research presents foundations for a reliable scheme for recovery from failure of workflow processes spanning through multiple business entities. First, a system model is adapted from the mobile computing literature that serves to establish the requirements to be enforced by each participating organization. In our model, we adopt the Maximal Sequence Path (MSP) approach from Yoo et al . (Lecture Notes in Artificial Intelligence 2132:222-236, ), as a means of decomposing workflows into mobile agent-driven processes that communicate via web services at each organization. This decomposition ensures defining logical points within the dynamics of a workflow instance for locating accurate and consistent states of the system for recovery in case of a failure. Then, a set of algorithms for various business scenarios are developed and presented as practical solutions. These algorithms are shown to create checkpoints such that the system is always in a globally consistent state. As such, these algorithms constitute a set of standards that can be incorporated in business process management suites that support reliable inter-organizational collaboration. [ABSTRACT FROM AUTHOR]

Abstract: Advancement in technology provides opportunities to user as well as challenges for application development organization. User interfaces which were design for specific device tend to be developed for various devices. Users are busy people, when they move among different context would like to move application with them. The current trend of users demanding mobile graphic user interface to support their daily life and work has led to a new generation of techniques. Design time technique provides better usability as compare to run time technique. On the other hand artificial intelligence technique like agent provides better flexibility and usability as compare to others. In this paper we have compared these techniques in the context of mobility of user interface. [Copyright &y& Elsevier]

The article presents a study on the collective social strategies for the diffusion of multiagents. It highlights the use of two kinds of diffusions which are the collective insurgence, as well as the elite diffusions that are modelled through setting the variables in the formal framework. It explores the concurrent forms of collective diffusion, while social strategies are determined by other diffusion processes on other agents. It focuses on the spatial diffusion model assuming that all agents can be found in an Euclidian space wherein the social distances between agents can be measured.

The connection with Wirth's book goes beyond the title, albeit confining the area to modern Artificial Intelligence (AI). Whereas thirty years ago, to devise effective programs, it became necessary to enhance the classical algorithmic framework with approaches applied to limited and focused subdomains, in the context of broad-band technology and semantic web, applications - running in open, heterogeneous, dynamic and uncertain environments-current paradigms are not enough, because of the shift from programs to processes. Beside the structure as position paper, to give more weight to some basic assertions, results of recent research are abridged and commented upon in line with new paradigms. Among the conclusions: a) Nondeterministic software is unavoidable; its development entails not just new design principles but new computing paradigms. b) Agent-oriented systems, to be effectual, should merge conventional agent design with approaches employed in advanced distributed systems (where parallelism is intrinsic to the problem, not just a mean to speed up). [ABSTRACT FROM AUTHOR]

We present a novel system that recognizes and records the motional activities of a person using a mobile phone. Wireless sensors measuring the intensity of motions are attached to body parts of the user. Sensory data is collected by a mobile application that recognizes prelearnt activities in real-time. For efficient motion pattern recognition of gestures and postures, feed-forward backpropagation neural networks are adopted. The design and implementation of the system are presented along with the records of our experiences. Results show high recognition rates for distinguishing among six different motion patterns. The recognized activity can be used as an additional retrieval key in an extensive mobile memory recording and sharing project. Power consumption measurements of the wireless communication and the recognition algorithm are provided to characterize the resource requirements of the system. [ABSTRACT FROM AUTHOR]

Abstract  The emergence of intelligent software agents that operate autonomously with little or no human intervention has generated many doctrinal questions at a conceptual level and has challenged the traditional rules of contract especially those relating to the intention as an essential requirement of any contract conclusion. In this paper, we will try to explore some of these challenges, and shed light on the conflict between the traditional contract theory and the transactional practice in the case of using intelligent software agents. We will try further to examine how intelligent software agents differ from other software applications, and consider then how such differences are legally relevant. This paper, however, is not intended to provide the final answer to all questions and challenges in this regard, but to identify the main components, and provide perspectives on how to deal with such issue. [ABSTRACT FROM AUTHOR]

We coordinate in discrete time the interaction of two heterogeneous groups of mobile agents: a group of ground vehicles (ugvs) and a group of aerial vehicles (uavs). The ground agents interact with each other through time-invariant, nearest-neighbour rules. They synchronize their velocities through a specific communication protocol, and maintain cohesion and separation behaviour by means of interagent potential forces. Ground vehicles estimate their formation’s centroid using only locally available delayed information. That same information is transmitted to the aerial group, which orbits above the ground formation’s centroid, while avoiding midair collisions. Stability of the ground group motion is established in a Lyapunov framework. A Lyapunov analysis is also used to ensure that uavs track the ground group’s centroid. [Copyright &y& Elsevier]

This article aims to present an account of the state of the art research in the field of integrated cognitive architectures by providing a review of six cognitive architectures, namely Soar, ACT-R, ICARUS, BDI, the subsumption architecture and CLARION. We conduct a detailed functional comparison by looking at a wide range of cognitive components, including perception, memory, goal representation, planning, problem solving, reasoning, learning, and relevance to neurobiology. In addition, we study the range of benchmarks and applications that these architectures have been applied to. Although no single cognitive architecture has provided a full solution with the level of human intelligence, important design principles have emerged, pointing to promising directions towards generic and scalable architectures with close analogy to human brains. [ABSTRACT FROM AUTHOR]

The potential utility of agent‐based models of adaptive, spatially aware, and mobile entities in geographic and ecological research is considerable. Developing this potential, however, presents significant challenges to geographic information science. Modelling the spatio‐temporal behaviour of individuals requires new representational forms that capture how organisms store and use spatial information. New procedures must be developed that simulate how individuals produce bounded knowledge of geographical space through experiential learning, adapt this knowledge to continually changing environments, and apply it to spatial decision‐making processes. In this paper, we present a framework for the representation of adaptive, spatially aware, and mobile agents. To provide context to this research, a multiagent model is constructed to simulate the migratory behaviour of elk (Cervus elaphus) on Yellowstone's northern range. In this simulated environment, intelligent agents learn in ways that enable them to mimic real‐world behaviours and adapt to changing landscapes. [ABSTRACT FROM AUTHOR]

This paper proposes a Content-Based Image Retrieval (CBIR) system applicable in mobile devices. Due to the fact that different queries to a content-based image retrieval (CBIR) system emphasize different subsets of a large collection of features, most CBIR systems using only a few features are therefore only suitable for retrieving certain types of images. In this research we combine a wide range of features, including edge information, texture energy, and the HSV color distributions, forming a feature space of up to 1053 dimensions, in which the system can search for features most desired by the user. Through a training process using the AdaBoost algorithm9 our system can efficiently search for important features in a large set of features, as indicated by the user, and effectively retrieve the images according to these features. The characteristics of the system meet the requirements of mobile devices for performing image retrieval. The experimental results show that the performance of the proposed system is sufficiently applicable for mobile devices to retrieve images from a huge database. [ABSTRACT FROM AUTHOR]

A recurring requirement for human-level artificial intelligence is the incorporation of vast amounts of knowledge into a software agent that can use the knowledge in an efficient and organized fashion. This article discusses representations and processes for agents and behavior models that integrate large, diverse knowledge stores, are long-lived, and exhibit high degrees of competence and flexibility while interacting with complex environments. There are many different approaches to building such agents, and understanding the important commonalities and differences between approaches is often difficult. We introduce a new approach to comparing frameworks based on the notions of commitment, reconsideration, and a categorization of representations and processes. We review four agent frameworks, concentrating on the major representations and processes each directly supports. By organizing the approaches according to a common nomenclature, the analysis highlights points of similarity and difference and suggests directions for integrating and unifying disparate approaches and for incorporating research results from one framework into alternatives. [ABSTRACT FROM AUTHOR]

PROSOCS agents are software agents that are built according to the KGP model of agency. KGP is used as a model for the mind of the agent, so that the agent can act autonomously using a collection of logic theories, providing the mind's reasoning functionalities. The behavior of the agent is controlled by a cycle theory that specifies the agent's preferred patterns of operation. The implementation of the mind's generic functionality in PROSOCS is worked out in such a way so it can be instantiated by the platform for different agents across applications. In this context, the development of a concrete example illustrates how an agent developer might program the generic functionality of the mind for a simple application. [ABSTRACT FROM AUTHOR]

The paper introduces some issues and related solutions adopted in order to realize the MMASS platform. This is a framework to specify and execute simulation applications based on the multi-layered multi-agent situated system model (MMASS). MMASS is a model for multi-agent systems (MAS) situated in an environment whose structure is explicitly defined. The behavior and interaction models of MMASS agents are strongly related to the spatial structure of their environment. The MMASS model is the result of a long-term research that has its roots and motivations on application domains and problems that require spatial features to be considered. Our experiences with these problems have concerned the design of domain models and their implementations, according to the MAS approach for simulation purposes. This activity has revealed that currently available tools do not support the management of spatial features of agent environment and interaction mechanisms defined by the MMASS model and thus they are not suitable for our purposes. The paper focuses on the MMASS platform that aims to support the specification and development of applications (mainly, simulations) based on MMASS. Design issues and related solutions that have been adopted in order to manage those aspects that characterize the MMASS model will be shown. After a description of the conceptual model that underlies the MMASS platform and its general architecture, we will overview how the platform supports the specification of agent structured environment, behavior and interaction, and how it supports the execution of agent actions and interactions. Then we will describe issues and adopted solutions (both algorithmic and implementative ones) to manage at-a-distance interaction among MMASS agents. [ABSTRACT FROM AUTHOR]

Enabling and managing coordination activities between autonomous, possibly mobile, computing entities in dynamic computing scenarios challenges traditional approaches to distributed application development and software engineering. This paper specifically focuses on the problem of motion coordination, and proposes field-based coordination as a general framework to model and engineer such coordinated behaviors. The key idea in field-based coordination is to have agents' movements driven by computational force fields, generated by the agents themselves and/or by some infrastructure, and propagated across the environment. This paper shows that field-based approaches enable the definition of adaptive and effective motion coordination schemes, which can be modeled and tested by making use of a dynamical systems formalism, and which can be easily implemented either above existing middleware infrastructures or by making use of novel middleware specifically conceived for field-based coordination. [ABSTRACT FROM AUTHOR]

The evolution of powerful portable networked devices allows nomadic users seamless access to business and leisure information any time and any where. This drives service infrastructures to similarly evolve to meet new service management challenges in order to adapt information delivery to a richer spatial, temporal, and user context whilst balancing the concerns of the different stakeholders. This paper presents the use of a multi-agent system service infrastructure and associated privacy model to maintain the balance between the service provider's need to maximize its knowledge of the user context against the need for the user's privacy to be protected. [ABSTRACT FROM AUTHOR]

Multi-agent systems are well suited for building large software systems. A great deal of these complex systems includes process flows that are concerned with time or are even time-critical. The activities of these process flows are often executed in distributed autonomous subsystems that have to be synchronized with respect to the superordinated task execution. To be able to build such systems and test their behavior adequately, it is often advantageous and sometimes necessary to simulate them in the run-up to their practical use. Testing and simulation of process flows within multi-agent systems requires synchronization of the participating agents with respect to the global simulation time. In this paper, a design proposal and a service implementation for time management is presented, which takes care of the special requirements imposed by multi-agent settings. This so-called time service is implemented as an FIPA-compliant agent, and can be used to couple heterogeneous subsystems implemented on different agent platforms. [ABSTRACT FROM AUTHOR]

In this paper we present the agent architecture development environment (ADE), intended for the design, implementation, and testing of distributed robotic agent architectures. ADE is unique among robotic architecture development environments in that it is based on a universal agent architecture framework called APOC, which allows it to implement architectures in any design methodology, and in that it uses an underlying multi-agent system to allow for the the distribution of architectural components over multiple host computers. After a short exposition of the theory behind ADE, we present the multi-agent system setup and give an example of using ADE in a multi-robot setting. A general discussion then highlights some of the novel features of ADE and illustrates how ADE can be used for designing, implementing, testing, and running agent architectures. [ABSTRACT FROM AUTHOR]

In order to harness complexity in multi-agent systems (MAS), first-class entities that mediate interaction between agents and environment are required, which can encapsulate control over MAS behavior and evolution. To this end, MAS infrastructures should provide mediating artifacts , both enabling and constraining agent interactions, and possibly representing admissible agent perceptions and actions over the environment. Along this line, in this paper, we take the notion of agent coordination context (ACC) as a means to model agent-environment interactions, and show how it can be embedded within a MAS infrastructure in terms of model and runtime structures. Then, we take the TuCSoN coordination infrastructure as a reference, and extend it with the ACC abstraction to integrate the support for coordination with organization and security. [ABSTRACT FROM AUTHOR]

Mobile agent paradigm is recognized as a new environment for distributed computing and provides many merits such as mobility, security, self-decision, and so on. However, its security problems should be resolved to increase its application to a variety of real domains. Especially, we must guarantee integrity of transferred mobile agents. Although many mobile agent systems were developed, the integrity issue remains a critical one. In this paper, we propose an integrity checking mechanism to do the aforementioned issue. The proposed mechanism is independent of specific security frameworks and can be added and used easily for various mobile agent platforms. [ABSTRACT FROM AUTHOR]

This paper investigates a human walking behavior- based mobile robot control system. The Intelligent Space (iSpace) is a distributed sensory system, which is the background infrastructure to observe human walking in a limited area. The observation of human walking behavior is applied to train fuzzy-neural networks (FNN). The trained FNNs are applied to approximate the obstacle avoidance behavior of human walking. The paper introduces the iSpace and the mobile agents, which are mobile robots, utilizing the intelligence of the iSpace. The observed and trained human walking behaviors are applied to control the mobile agent in a human-robot shared environment. Experimental results demonstrate the effectiveness of the FNN-based control system. [ABSTRACT FROM AUTHOR]

The ability for a given agent to adapt on-line to better interact with another agent is a difficult and important problem. This problem becomes even more difficult when the agent to interact with is a human, because humans learn quickly and behave nondeterministically. In this paper, we present a novel method whereby an agent can incrementally learn to predict the actions of another agent (even a human), and thereby can learn to better interact with that agent. We take a case-based approach, where the behavior of the other agent is learned in the form of state–action pairs. We generalize these cases either through continuousk-nearest neighbor, or a modified bounded minimax search. Through our case studies, our technique is empirically shown to require little storage, learn very quickly, and be fast and robust in practice. It can accurately predict actions several steps into the future. Our case studies include interactive virtual environments involving mixtures of synthetic agents and humans, with cooperative and/or competitive relationships. [ABSTRACT FROM AUTHOR]

Artificial intelligence researchers have been attracted by the idea of having robots learn how to accomplish a task, rather than being told explicitly. Reinforcement learning has been proposed as an appealing framework to be used in controlling mobile agents. Robot learning research, as well as research in biological systems, face many similar problems in order to display high flexibility in performing a variety of tasks. In this work, the controlling of a. vehicle in an avoidance task by a previously developed operant learning model (a form of animal learning) is studied. An environment in which a mobile robot with proximity sensors has to minimize the punishment for colliding against obstacles is simulated. The results were compared with the Q-Learning algorithm, and the proposed model had better performance. In this way a new artificial intelligence agent inspired by neurobiology, psychology, and ethology research is proposed. [ABSTRACT FROM AUTHOR]

A problem specific to mobile agent systems is that the basis of trustworthiness cannot be ensured. Even during the information gathering stage, it may not be possible to gather information correctly if a host computer is providing false information or if the agent has a bug or has been corrupted. In other words, it is important to ascertain where faults can occur or what can be trusted. Although voting methods have already been proposed for these purposes, the waiting or centralized processing required for voting may ruin the distributed characteristic of a mobile agent system. In the present research, the authors use a dynamic relationship network, which is proposed as a distributed diagnosis model, to execute decentralized evaluations of the credibility of each host and agent in an information gathering system. They use simulations to verify the kinds of parameters needed as a basis for performing credibility evaluations appropriately. They also examine test methods for handling information scattering (probability-based properties). © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(9): 10–19, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10427 [ABSTRACT FROM AUTHOR]

The article presents the conclusions and lessons learned at the 2005 AAMAS Industry Track, the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems. Hindrances in the industrial adoption of agent-based solutions are offered, including limited awareness of agent technology's potential, limited publicity of successful projects, and misunderstandings about agent technology's capabilities. It also discusses seven main categories of common unrealistic expectations and inappropriate uses of agent technology, namely, complexity, black box, intelligence, agentification, learning, interoperability, and mobility.

The article discusses multiagent systems and autonomous-agent technologies which provides industrial applications-developers with new design-and-implementation model for software solutions and a wide range of ready-to-use technologies, development platforms, and techniques and algorithms. The performance of agent paradigm and the available agent techniques in five types of domains are discussed. It presents the events at the Industry Track of AAMAS 2005 - the Fourth International Joint Conference on Autonomous and Multiagent Systems.