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With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a growing demand for developing a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method.

This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents.

By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment.

This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.

Marketing management presents challenging ground for the integrated use of intelligent agents. The design of a strategic marketing plan presents a natural division of four distinct yet independent decision problems. Concurrent execution of these four functions can yield a significant decrease in time‐to‐market for new products, and turnaround time for modified products. Electronic information is a two‐edged sword. On the one hand, it results in information overload, taxing the decision‐ making process. On the other hand, the electronic nature of these vast information flows makes them accessible to intelligent agents who can improve the decision‐making process. This paper presents the problem of information overload and decision‐making complexity in marketing management. In it, we present a blackboard‐based agent architecture that allows individual agents to proceed toward their given goals yet react opportunistically to developments reported by other marketing agents. We present the blackboard model of problem solving, and discuss why it is well suited to support multiple marketing agents. CMA, a multi‐agent model for concurrent marketing analysis, is discussed and the agent architecture required for creating a cooperating society of marketing agents is presented.

High-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.

This paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.

The findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.

This study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

This paper aims to present an approach for the simulation of a heterogeneous robotic cell. The simulation enables the cell’s developers to conveniently compare the performance of alternative cell configurations. The approach combines the use of multiple available simulation tools, with a custom holonic cell controller. This overcomes the limitation of currently available robot simulation packages by allowing integration of multiple simulation tools including multiple vendor simulation packages.

A feeding cell was developed as a case study representing a typical robotic application. The case study would compare two configurations of the cell, namely, eye-in-hand vision and fixed-camera vision. The authors developed the physical cell in parallel with the simulated cell to validate its performance. Then they used simulation to scale the models (by adding subsystems) and shortlist suitable cell configurations based on initial capital investment and throughput rate per unit cost. The feeding cell consisted of a six-degree of freedom industrial robot (KUKA KR16), two smart cameras (Cognex ism-1100 and DVT Legend 500), an industrial PC (Beckhoff) and custom reconfigurable singulation units.

The approach presented here allows the combination of dissimilar simulation models constructed for the above mentioned case study. Experiments showed the model developed in this approach could reasonably predict various eye-in-hand and fixed-camera systems’ performance. Combining the holonic controller with the simulation allows developers to easily compare the performance of a variety of configurations. The use of a common communication platform allowed the communication between multiple simulation packages, allowing multi-vendor simulation, thereby overcoming current limitation in simulation software.

The case study developed here is considered a typical feeding and assembly application. This is however very different from other robotic applications which should be explored in separate case studies. Simulation packages with the same communication interface as the physical resource can be integrated. If the communication interface is not available, other means of simulation can be used. The case study findings are limited to the specific products being used and their simulation packages. However, these are indicative of typical industry technologies available. Only real-time simulations were considered.

This simulation-based approach allows designers to quickly quantify the performance of alternative system configurations (eye-in-hand or fixed camera in this case) and scale, thereby enabling them to better optimize robotic cell designs. In addition, the holonic control system’s modular control interface allows for the development of the higher-level controller without hardware and easy replacement of the lower level components with other hardware or simulation models.

The combination of a holonic control system with a simulation to replace hardware is shown to be a useful tool. The inherent modularity of holonic control systems allows that multiple simulation components be connected, thereby overcoming the limitation of vendor-specific simulation packages.

The purpose of this chapter is to offer reflections on conventional theories concerning causes and determinants of diseases. It also intends to examine both theoretical and empirical bases for adopting an Integrated Social-Ecological Systems (ISES) lens as a tool for understanding complexities related to drivers, determinants and causes of diseases.

We assessed the theoretical underpinnings of a range of historical and contemporary lenses for viewing infectious disease drivers and the implications of their use when used to explain both personal (i.e. individual) and population health. We examined these issues within the empirical context of the City of Dhaka (Bangladesh) by adopting an ISES lens. Within this study an emphasis has been placed on illustrating how feedback loops and non-linearity functions in systems have a direct bearing upon various aspects of infectious disease occurrences.

A brief triumph over microbes during the last century stemmed in part from our improved understanding of disease causation which was built using disciplinary-specific, monocausal approaches to the study of disease emergence. Subsequently, empirical inquiries into the multi-factorial aetiology and the ‘web of causation’ of disease emergence have extended frameworks beyond simplistic, individualistic descriptions of disease causation. Nonetheless, much work is yet to be done to understand the roles of complex, intertwined, multi-level, social-ecological factors in affecting disease occurrence. We argue, a transdisciplinary-oriented, ISES lens is needed to explain the complexities of disease occurrence at various and interacting levels. More theoretical and empirical formulations, with evidence derived from various parts of the world, is also required to further the debate.

Our study advances the theoretical as well as empirical basis for considering an integrated human-nature systems approach to explaining disease occurrence at all levels so that factors at the individual, household/neighbourhood, local, regional and global levels are not treated in isolation.

The purpose of this paper is to review the current state of proceedings in the research area of automatic swarm design and discusses possible solutions to advance swarm robotics research.

First, this paper begins by reviewing the current state of proceedings in the field of automatic swarm design to provide a basic understanding of the field. This should lead to the identification of which issues need to be resolved in order to move forward swarm robotics research. Then, some possible solutions to the challenges are discussed to identify future directions and how the proposed idea of incorporating learning mechanism could benefit swarm robotics design. Lastly, a novel evolutionary-learning framework for swarms based on epigenetic function is proposed with a discussion of its merits and suggestions for future research directions.

The discussion shows that main challenge which is needed to be resolved is the presence of dynamic environment which is mainly caused by agent-to-agent and agent-to-environment interactions. A possible solution to tackle the challenge is by incorporating learning capability to the swarm to tackle dynamic environment.

This paper gives a new perspective on how to improve automatic swarm design in order to move forward swarm robotics research. Along with the discussion, this paper also proposes a novel framework to incorporate learning mechanism into evolutionary swarm using epigenetic function.

In the vision of pervasive computing, numerous heterogeneous devices, various information services, and users performing daily activities are physically co‐located in a environment. How can we coordinate the services and devices to assist a particular user in receiving a particular service so as to maximize the user’s satisfaction? To solve this human‐centered coordination issue, we propose an agent‐based service coordination framework for pervasive computing. It is called location‐aware middle agent framework. The middle agent takes account of the user location in cognitive way (based on location‐ontology), and determines best‐matched services for the user. Based on this coordination framework, we have developed a multi‐agent architecture for pervasive computing, called CONSORTS (Coordination System of Real‐world Transaction Services). In this paper, we first outline some requirements of the human‐centered service coordination in pervasive computing. Secondly, we describe location‐aware middle agent framework to fill the requirements. Lastly, we outline CONSORTS, an prototype of location‐aware middle agent framework, and two applications of CONSORTS, location‐aware information assistance services in a museum and wireless‐LAN based location systems on FIPA agent Networks.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

A general framework for mobile Web services ‐ which are Web services with the ability to migrate from one host to another ‐ is proposed. In this framework, a mobile Web service is composed of a combination of a BPEL process description, service components to be carried, and migration behavior descriptions using simple but expressive rules. The semantics of the descriptions are defined using Mobile Ambients, namely, a formal model of concurrent mobile processes. With this framework, it is thus possible to add or change migration behaviors without having to modify the BPEL process.

The purpose of this paper is to propose an approach that integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning. Unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today’s supply chains. In addition, a few existing agent-based approaches are tied to real-world supply chain functions like supplier selection. These approaches are static and do not adequately take the qualitative and quantitative factors into consideration. Therefore, an agent-based framework is needed to address these issues.

The proposed approach integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning, as a common framework. These perspectives were rarely used together as a common framework in previous studies. Furthermore, an exploratory case study in an office furniture company is undertaken to illustrate the value of the framework.

The proposed agent-based framework evaluates supply offers based on customers’ preferences, recommends alternative products in the case of stock-out and provides a collaborative environment among agents who represent different supply chain entities. The proposed fuzzy case-based reasoning (F-CBR) approach reduces the information overload by organizing them into the relevant cases that causes less overall search between cases. In addition, its fuzzy aspect addresses the high uncertainty of supply chains, especially when there are different customers’ orders with different preferences.

The present study does not include the functions of inventory management and negotiation between agents. Furthermore, only the case description and case retrieval phases of the case-based reasoning approach are investigated, and the remaining phases like case retaining, case reusing and case revising are not included in the scope of this paper.

This framework balances the interests of different supply chain structural elements where each of them is represented by a specific agent for better collaboration, decision-making and problem-solving in a multi-agent environment. In addition, the supplier selection and order gathering mechanisms are developed based on customers’ orders.