Fuzzy approaches to the game of Chicken

Game theory deals with decision-making processes involving two or more parties, also known as players, with partly or completely conflicting interests. Decision-makers in a conflict must often make their decisions under risk and under unclear or fuzzy information. In this paper, two distinct fuzzy approaches are employed to investigate an extensively studied 2×2 game model-the game of Chicken. The first approach uses a fuzzy multicriteria decision analysis method to obtain optimal strategies for the players. It incorporates subjective factors into the decision-makers' objectives and aggregates objectives using a weight vector. The second approach applies the theory of fuzzy moves (TFM) to the game of Chicken. The theory of moves (TOM) is designed to bring a dynamic dimension to the classical theory of games by allowing decision-makers to look ahead for one or several steps so that they can make a better decision. TOM is the crisp counterpart of TFM, the approach we implement here to deal with games that include fuzzy and uncertain information. The application of fuzzy approaches to the game of Chicken demonstrates their effectiveness in manipulating subjective, uncertain, and fuzzy information and provides valuable insights into the strategic aspects of Chicken     

A Framework for Coordinated Control of Multiagent Systems and Its Applications

In this paper, a framework is proposed for the distributed control and coordination of multiagent systems (MASs). In the proposed framework, the control of MASs is regarded as achieving decentralized control and coordination of agents. Each agent is modeled as a coordinated hybrid agent, which is composed of an intelligent coordination layer and a hybrid control layer. The intelligent coordination layer takes the coordination input, plant input, and workspace input. In the proposed framework, we describe the coordination mechanism in a domain-independent way, i.e., as simple abstract primitives in a coordination rule base for certain dependence relationships between the activities of different agents. The intelligent coordination layer deals with the planning, coordination, decision making, and computation of the agent. The hybrid control layer of the proposed framework takes the output of the intelligent coordination layer and generates discrete and continuous control signals to control the overall process. To verify the feasibility of the proposed framework, experiments for both heterogeneous and homogeneous MASs are implemented. The proposed framework is applied to a multicrane system, a multiple robot system, and a MAS consisting of an overhead crane, a mobile robot, and a robot manipulator. It is demonstrated that the proposed framework can model the three MASs. The agents in these systems are able to cooperate and coordinate to achieve a global goal. In addition, the stability of systems modeled using the proposed framework is also analyzed.     

CONCORD: A Control Framework for Distributed Real-Time Systems

Novel network technology combined with advances in hardware development have permitted the enabling of distributed real-time systems and have shortened the time-to-market period. Distributed frameworks, also known as middleware, are often used to integrate enterprise systems, shorten the development time, and reduce complexity. However, to deploy standard middleware in robotics and control applications, we have to deal with the challenge of producing predictable outputs. Most real-time applications in these areas are developed in ad hoc manner, and as such, it is hard to migrate them to new platforms. To overcome this issue while minimizing development effort and increasing reusability for distributed real-time systems, we propose a control framework for distributed real-time systems based on standard middleware specifications. The control framework is composed of asynchronously running task modules, which can be located on either the local or the remote machines. The task modules are connected by an event channel, which uses the publish/subscribe communication method. We also have developed an adaptive event channel in order to meet real-time system requirements and to produce predictable outputs. Detailed development of the control framework along with the adaptive event channel are assessed through a set of experimental results.     

An efficient concept-based retrieval model for enhancing text retrieval quality

Most of the common techniques in text retrieval are based on the statistical analysis terms (words or phrases). Statistical analysis of term frequency captures the importance of the term within a document only. Thus, to achieve a more accurate analysis, the underlying model should indicate terms that capture the semantics of text. In this case, the model can capture terms that represent the concepts of the sentence, which leads to discovering the topic of the document. In this paper, a new concept-based retrieval model is introduced. The proposed concept-based retrieval model consists of conceptual ontological graph (COG) representation and concept-based weighting scheme. The COG representation captures the semantic structure of each term within a sentence. Then, all the terms are placed in the COG representation according to their contribution to the meaning of the sentence. The concept-based weighting analyzes terms at the sentence and document levels. This is different from the classical approach of analyzing terms at the document level only. The weighted terms are then ranked, and the top concepts are used to build a concept-based document index for text retrieval. The concept-based retrieval model can effectively discriminate between unimportant terms with respect to sentence semantics and terms which represent the concepts that capture the sentence meaning. Experiments using the proposed concept-based retrieval model on different data sets in text retrieval are conducted. The experiments provide comparison between traditional approaches and the concept-based retrieval model obtained by the combined approach of the conceptual ontological graph and the concept-based weighting scheme. The evaluation of results is performed using three quality measures, the preference measure (bpref), precision at 10 documents retrieved (P(10)) and the mean uninterpolated average precision (MAP). All of these quality measures are improved when the newly developed concept-based retrieval model is used, confirming that such model enhances the quality of text retrieval.     

Classification of underground pipe scanned images using featureextraction and neuro-fuzzy algorithm

Pipeline surface defects such as holes and cracks cause major problems for utility managers, particularly when the pipeline is buried under the ground. Manual inspection for surface defects in the pipeline has a number of drawbacks, including subjectivity, varying standards, and high costs. Automatic inspection system using image processing and artificial intelligence techniques can overcome many of these disadvantages and offer utility managers an opportunity to significantly improve quality and reduce costs. A recognition and classification of pipe cracks using images analysis and neuro-fuzzy algorithm is proposed. In the preprocessing step the scanned images of pipe are analyzed and crack features are extracted. In the classification step the neuro-fuzzy algorithm is developed that employs a fuzzy membership function and error backpropagation algorithm. The idea behind the proposed approach is that the fuzzy membership function will absorb variation of feature values and the backpropagation network, with its learning ability, will show good classification efficiency.     

Analytical expressions for blocking and dropping probabilities for mobile streaming users in wireless cellular networks

We consider a wireless cellular network serving streaming traffic. We study in this context the effect of the users mobility on their quality of service (QoS). If the arrival of a new user violates the capacity constraint, then his call is blocked. If the user is first admitted but the capacity constraint is violated later when he attempts to move, then his call is dropped. The blocking and dropping probabilities are the main QoS indicators in this model called forced termination (FT). We introduce an alternative model, called transitions backtrack (TB), where a user backtracks when his motion violates the capacity constraint. In this model, a relevant QoS indicator is the number of times the user backtracks called number of motion blocking per call. We propose some explicit expressions for the above QoS indicators as functions of the mean user speed. These expressions are validated by simulations. In particular we observe that the dropping probability in the FT model is well approximated by the number of motion blocking per call in the TB model which is expressed analytically.     

A general formulation for the nonlinear dynamics and control of orbiting flexible structures

A relatively general Lagrangian formulation for studying the dynamics of a large class of spacecraft characterized by interconnected flexible members forming a tree topology, is presented. Methodology and development of the computer code suitable for parametric dynamical study and control are briefly outlined. Versatility of the general formulation is demonstrated through dynamics studies of the Permanently Manned Configuration (PMC) of the proposed Space Station Freedom and the slewing dynamics and control of the two-link Mobile Servicing System (MSS) aboard Freedom. The PMC study indicates the effect of flexibility cannot be overlooked. Even a small disturbance on the main or stinger can result in unacceptable magnitudes of velocity and acceleration. The MSS study compares the system response subjected to the InPlane (IP) and Out-of-Plane (OP) maneuvers. Results indicate that, without control, the OP maneuver excites large yaw motion of the Space Station. Consequently, the OP maneuver has a large pointing error. Nonlinear control, based on the Feedback Linearization Technique, appears promising. By controlling the librational motion of the station, the performance of the OP maneuver improves significantly.     

Soft-Computing-Based Embedded Design of an Intelligent Wall/Lane-Following Vehicle

Soft computing techniques are generally well suited for vehicular control systems that are usually modeled by highly nonlinear differential equations and working in unstructured environments. To demonstrate their applicability in real-world applications, two intelligent controllers based on fuzzy logic and artificial neural network are designed for performing a wall-following task. Based on performance and flexibility considerations, the two controllers are implemented onto a reconfigurable hardware platform, namely a field-programmable gate array. As comparative studies of these two embedded hardware controllers designed for the same vehicular application are limited in literature, this research also presents an evaluation of the two controllers, comparing them in terms of hardware resource requirements, operational speeds, and trajectory tracking errors in following different predefined trajectories.     

PROMES: An ontology‐based messaging service for semantically interoperable information exchange during disaster response

Disaster response requires the cooperation of multiple emergency responder organizations (EROs). However, after‐action reports relating to large‐scale disasters identity communication difficulties among EROs as a major hindrance to collaboration. On the one hand, the use of two‐radio communication, based on multiple orthogonal frequencies and uneven coverage, has been shown to degrade inter‐organization communication. On the other hand, because they reflect different areas of expertise, EROs use differing terminologies, which are difficult to reconcile. These issues lead to ambiguities, misunderstandings, and inefficient exchange of data and information among those involved, which can impede the response process and slow decision making. We, therefore, hypothesize that promoting semantic interoperability across ERO information systems might improve information exchange among stakeholders and thereby allow a more coherent response to the disaster. We propose an ontology‐based messaging service on the basis of the Emergency Data Exchange Language (EDXL) standards. The parties involved will continue to use the terminologies to which they are accustomed, but the system will resolve inconsistencies and thereby enhance mutual understanding among EROs by ensuring semantic translation of the exchanged information. The evaluation of the semantic translation demonstrated the effectiveness and accuracy of the proposed service.