FuzzyOrganization of Self-Adaptive Agents Based On Software Components

In recent years, the topic of emotion reading has increasingly received attention from researchers in Cognitive Science and Artificial Intelligence. To study this phenomenon, in this paper an adaptive agent model is presented with capabilities to interpret another agent’s emotions. The presented agent model is based on recent advances in neurological context. First a non-adaptive agent model for emotion reading is described involving (preparatory) mirroring body states of the other agent. Here emotion reading is modelled taking into account the Simulation Theory perspective as known from the literature, involving the own body states and emotions in reading somebody else’s emotions. This models an agent that first develops the same feeling, and after feeling the emotion imputes it to the other agent. Next the agent model is extended to an adaptive model based on a Hebbian learning principle to develop a direct connection between a sensed stimulus concerning another agent’s body state (e.g., face expression) and the emotion recognition state. In this adaptive agent model the emotion is imputed to the other agent before it is actually felt. The agent model has been designed based on principles of neural modelling, and as such has a close relation to a neurological realisation.Keywordsagent modelemotion readingcognitivetheory of mindadaptive

Maintenance accounts for a major cost of software development. The design of software systems from the very beginning phase to achieve adaptive behaviour should, therefore, be recognised of its importance in practice. Adaptive Agent Model (AAM) is aimed towards this end via using Agent-oriented Model-Driven Architecture. Models are derived from requirements and reconfigured continuously by domain experts to reflect changing business needs. Agents interpret these models, at runtime, to choose alternative partners in collaboration or reusable components in computation, in an adaptive manner. Adopting an event-driven architecture at runtime, AAM has its agents and knowledge-based control readily applicable to robots and their on-board control extension. The paper describes work towards this goal and ultimately, this will demonstrate the feasibility of AAM in software adaptivity via the robot platform, and also help to achieve robot adaptivity through corresponding AAM support.

PurposeThe purpose of this paper is to design a new method to realize automatic assembly of aircraft components with large shafts such as canard and vertical tail. The assembly structure of component with large shaft and fuselage is a mating assembly structure, and it is a challenge to satisfy the precision and assembly requirement.Design/methodology/approachAccording to the assembly structure features and process requirements of an aircraft component with large shaft, the operating principle of precise assembly system for shaft-hole mating is analyzed in this paper. The model of compliant assembly for shaft-hole mating is constructed, and force condition analysis of the compliant assembly is performed. An automatic precise shaft-hole assembly method for aircraft assembly using 5 degrees of freedom spatial mechanism, compliance technology and servo feeding system is put forward based on the analysis. A 5 degrees of freedom passive compliant experimental equipment has been developed.FindingsApplication test results of the 5 degrees of freedom passive compliant experimental equipment show that the simulated canard can be mated automatically and accurately through this method with high efficiency and high quality as long as the tip of shaft enters into the range of hole’s chamfer.Practical implicationsThis method has been used in an aircraft assembly project. The practical results show that the aircraft components with large shafts can be mated automatically and accurately through this method with high efficiency and high quality.Originality/valueThis paper presents a new method and designs a new assembly system to realize the assembly of the aircraft components with large shafts. The research will promote the automation of fuselage assembly.

Program Control Language: a programming language for adaptive distributed applications

Inspired by the work of Elaine Aron, in this paper a human-like adaptive computational agent model of the internal processes of a highly sensitive person (HSP) is presented. This agent model was used to get a better understanding of what goes wrong in these internal processes once this person gets upset. A scenario is addressed where a highly sensitive person will get upset by an external stimulus and will not be able to calm down by herself. Yet in a social context the interaction with a second person (without high sensitivity) will calm the HSP down, thus contributing to regulation. To obtain an adaptive model a Hebbian learning connection was integrated. During interaction with a second person this Hebbian learning link will become stronger, which makes it possible for a HSP to become independent after some time and be able to regulate upsetting external stimuli all by herself.

In this paper an adaptive agent model is presented that models how recurrent dreams such as nightmares occur. In the agent model recurring dreams emerge as scripts of connected dream episodes in which the connections between the episodes strengthen over time by Hebbian learning. The model was evaluated by a number of simulation experiments.

Conversational agents have been widely adopted in dialogue systems for various business purposes. Many existing conversational agents are rule-based and require significant human intervention to adapt the knowledge and conversational flow. In this paper, we propose a graph-based adaptive conversational agent model which is capable of learning knowledge from human beings and adapting the knowledge-base according to human-agent interactions. Studies to evaluate the proposed model are conducted and presented, which compare the responses from the proposed adaptive agent model and a conventional agent.

Correct automatic assembly in software components is an important issue in CBSE (Commercial-Off-The-Shelf). Building a system from reusable software components or from COTS (Commercial-Off-The-Shelf) components introduces a set of problems. One of the main problems in components assembly is related to the ability to properly manage the dynamic interactions of the components. Component assembling can result in architectural mismatches when trying to integrate components with incompatible interaction behavior like deadlock and other software anomalies. This problem represents a new challenge for system developers. The issue is not only in specifying and analyzing a set of properties rather in being able to enforce them out of a set of already implemented (local) behaviors. Our answer to this problem is a software architecture based approach in which the software architecture imposed on the assembly allows for detection and recovery of COTS integration anomalies. Starting from the specification of the system to be assembled and of its properties we develop a framework which automatically derives the glue code for the set of components in order to obtain a properties-satisfying system (i.e. the failure-free version of the system).

A special issue on ‘the emergence of language: neural and adaptive agent models’

Using agent development tools to construct an agent-based system is a popular approach. However, the developed agent system might not be feasible due to certain mutual conflicted rules stored in various agents. Currently, the development tools do not have the function to check the feasibility about the workflow of the agent system during it implementation stage. Therefore, in this research, a Petri Net (PN) based evaluation approach was developed. There were three stages in the proposed system. In the conceptual stage, the pitfall of the current agent system developing process was examined and an improvement analysis process was specified. Then, in the system design stage, an evaluation approach which extracted the process log file from a developing agent system into a PN model in terms of a process mining approach-α algorithm was proposed. This model was simulated in a PN simulation package. The agent system performance was evaluated in terms of analyzing the deadlock phenomena of the PN model. Finally, in the implementation stage, the proposed concept was implemented by using an agent developing tool JADE and a PN simulation tool CPN. An agent-based robotic assembly system was used to examine the possible deadlock of the agent system.KeywordsAgent SystemBase Evaluation ApproachProcess Mining ApproachAgent System PerformanceMessage FileThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The interest behind the use of component based software engineering is to divide an information system in subsystems with less complexity, the reduction of time, faster development, and enhancing the productivity. The software systems are developed by assembling components which are software units that offer a set of services exposed as interfaces. The indispensable role of component-based development is the component model that defines how components can be built and how they can be assembled. A component is intended to provide specific services as the management of the combination and the communication between the system units. The Manager Component is an important and complementary paradigm for the development of software systems. The functionalities that it encapsulates must be related and consistent. The model presented in this paper proposes a component called Manager Software component based on the viewpoint (vision of each system user and actor) by the assembly of Base Component and system components.

As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.

We investigate an evolution model of adaptive self-learning agents. The control system of agents is based on a neural network adaptive critic design. Each agent is a broker that predicts stock price changes and uses its predictions for action selection. We analyzed different regimes of learning and evolution and demonstrated that 1) evolution and learning together are more effective in searching for the optimal agent policy than evolution alone or learning alone; 2) in some regimes the Baldwin effect (genetic assimilation of initially acquired adaptive learning features during the course of Darwinian evolution) is observed; 3) inertial switching between two behavioral tactics similar to searching adaptive behavior of simple animals takes place during initial stages of evolutionary processes.KeywordsStock PriceAgent ResourceAdaptive AgentBaldwin EffectGenetic AssimilationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This paper presents a model of business improvement management of the company's organizational system. This model is implemented through the developed structural and logical model of value management of the organizational system, based on the concepts of the World and Russian Quality Awards and the ISO 9000 series standards. It presents tools such as cultural regulation, rules of joint activity, motivation system, administrative regulation and evaluation of the implementation of concepts for improving the company's organizational system. The formalization of the management model, which takes into account all the factors influencing sustainable development, is a multi-stage mathematical model that works with a given tolerance to achieve the planned criteria in a continuous mode. The criteria for the development of the company's organizational system are formed based on the strategy and policy in accordance with the accumulated experience. Based on the analysis of the previous five-year development and modern capabilities of the company's organizational system, a strategic indicator of the degree of development is determined for each criterion. With the help of the proposed model, an assessment is made for: - integral indicators of the company's organizational system in relation to working with the consumer; - indicators of total leadership of the organizational system and its personnel; - indicators of the total use of the talent and creativity of the staff; - integral indicators of the flexibility of the organization's management. The proposed model of business improvement management of the company's organizational system allows to: - flexibly organize the optimal effective work of the company's organizational system, using the most relevant tools; - continuously evaluate the effectiveness of the development of the company's organizational system in accordance with modern concepts of business improvement.

A flexible robotic work cell for the assembly of airframe components is described. The key cell devices are two robots, a flexible fixture, a metrology system, an automatic fastening machine, and several end effectors. Software modules are found behind all cell devices. Other software components are found in the cell controller, planning utilities, and offline programming. The emphasis is on functional aspects of the cell and the associated software. >