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Two large sample surveys of chief information officers (CIOs) were sponsored by Arthur Andersen & Co. in the last three years to analyze the market served by its consulting practice. Beginning in April of 1986, and then again in February of 1988, samples of 120 companies representing both the service and industrial segments of the Fortune 500 were selected. CIOs from those organizations were interviewed on issues, trends, and problems in the deployment of information technology (IT) within their corporation. A clear profile of evolving CIO responsibilities and the roles that information and technology played in those organizations emerged from these surveys. Below we have summarized the results of each study, and outlined the concerns of the CIOs who were given the task of establishing IT plans. We then go on to offer some advice to general management for overcoming obstacles that we see as inherent in executing such plans.

Fundamental changes in product, process, and organization have rocked the manufacturing industry of this country during the last decade. In an effort to document the nature and extent of these changes, we conducted a survey of senior manufacturing executives. We wanted to determine exactly how U.S. manufacturing companies were changing and why. Our specific goals were to document the nature and extent of technological change that has occurred since 1980; to determine the likely direction of change through 1990; and to compile opinions on the strategic issues facing the industry as well as on the keys to success in dealing with these issues.

This paper aims to discuss traffic patterns generated by swarms of robots while commuting to and from a base station.

The paper adopts a mathematical evaluation and robot swarm simulation. The swarm approach is bottom‐up: designing individual agents the authors are looking for emerging group behaviour patterns. Examples of group behaviour patterns are human‐driven motorized traffic which is rigidly structured in two lanes, while army ants develop a three‐lane pattern in their traffic. The authors copy army ant characteristics onto their robots and investigate whether the three lane traffic pattern may emerge. They follow a three‐step approach. The authors first investigate the mathematics and geometry of cases occurring when applying the artificial potential field method to three “perfect” robots. Any traffic pattern (two, three or more lanes) appears to be possible. Next, they use the mathematical cases to study the impact of limited visibility by defining models of sensor designs. In the final step the authors implement ant inspired sensor models and a trail following mechanism on the robots in the swarm and explore which traffic patterns do emerge in open space as well as in bounded roads.

The study finds that traffic lanes emerge in the swarm traffic; however the number of lanes is dependent on the initial situation and environmental conditions. Intrinsically the applied robot models do not determine a specific number of traffic lanes.

The paper presents a method for studying and simulating robot swarms.

The Group of Unmanned Assistant Robots Deployed in Aggregative Navigation by Scent (GUARDIANS) multi‐robot team is to be deployed in a large warehouse in smoke. The team is to assist firefighters search the warehouse in the event or danger of a fire. The large dimensions of the environment together with development of smoke which drastically reduces visibility, represent major challenges for search and rescue operations. The GUARDIANS robots act alongside a firefighter and guide and accompany the firefighters on the site while indicating possible obstacles and the locations of danger and maintain communications links. The purpose of this paper is to focus on basic navigation behaviours of multi‐robot or human‐robot teams, which have to be achieved without central and on‐line control in both categories of GUARDIANS robots' tasks.

In order to fulfill the aforementioned tasks, the robots need to be able to perform certain behaviours. Among the basic behaviours are capabilities to stay together as a group, that is, generate a formation and navigate while keeping this formation. The control model used to generate these behaviours is based on the so‐called social potential field framework, which the authors adapt to the specific tasks required for the GUARDIANS scenario. All tasks can be achieved without central control, and some of the behaviours can be performed without explicit communication between the robots.

The GUARDIANS environment requires flexible formations of the robot team: the formation has to adapt itself to the circumstances. Thus, the application has forced the concept of a formation to be re‐defined. Using the graph‐theoretic terminology, it can be said that a formation may be stretched out as a path or be compact as a star or wheel. The developed behaviours have been implemented in simulation environments as well as on real ERA‐MOBI robots commonly referred to as Erratics. Advantages and shortcomings of the model, based on the simulations as well as on the implementation with a team of Erratics are discussed.

This paper discusses the concept of a robot formation in the context of a real world application of a robot team (Swarm).

The purpose of this paper is to propose a model for a target searching problem in a two-dimensional region with time constraints. The proposed model facilitates the search operation by minimizing the mission time and fuel usage, and the search operation is performed by a set of agents divided into a number of groups.

The authors have applied optimization techniques, Cartesian product, inclusion–exclusion principle, cooperative strategy, Shapley value, fuzzy Shapley function and Choquet integral to model the problem.

The proposed technique optimizes the placement of base stations that minimizes the sortie length of the agents. The results show that the cooperative strategy outperforms the non-cooperative strategy. The Shapley values quantify the rewards of each group based on their contributions to the search operation, whereas the fuzzy Shapley values determine the rewards of each group based on their contributions and level of cooperation in the search operation.

The proposed model can be applied to model many real-time problems such as patrolling in international borders, urban areas, forests and managing rescue operations after natural calamities, etc. Therefore, defence organizations, police departments and other operation management sectors will be benefitted by applying the proposed approach.

To the best of the authors’ knowledge, determining the optimal locations of base stations in a region is not explored in the existing works on target searching problems with fuel constraints. The proposed approach to cooperatively search the targets in a region is new. Introducing the Shapley function and fuzzy Shapley function is a novel idea to quantify the rewards of each group based on their contributions and level of cooperation in the search operation. This paper addresses these unexplored areas.