Intelligent Agents

Los agentes inteligentes autónomos, debido a su proactividad, se ven obligados a considerar la satisfacción de sus metas a través de un conjunto estructurado de acciones que conforman un plan. El modelo BDI (Belief, Desires and Intentions)[8] para representar el conjunto cognitivo de un agente es una posibilidad interesante que permite estudiar el problema que introduce el dinamismo natural del entorno en el que un plan particular se desenvuelve. El entorno corriente, el mundo actual del agente, es representado con un modelo de creencias (beliefs) adecuado. Las metas del agente representan sus deseos (desires) y describen en forma parcial estados del entorno preferidos. Finalmente, los planes para alcanzar alguno de aquellos estados constituyen, en cierta forma, las intenciones (intentions).

Modern decision support systems (DSS) not only store large amounts of decision-relevant data, but also aim at assisting decision-makers to explore the meaning of that data, and to take decisions based on understanding. In transportation domains, a multiagent approach to the construction of DSS is becoming increasingly popular, because it does not only reduce design complexity, but it also adequately supports a dialogue-based stance on decision support interactions. However, despite recent advances in the field of agent-oriented software engineering, a principled approach to the design of multiagent systems for decision support is still to come. In this paper, we outline a design method for the construction of agent-based DSS. Setting out from an organisational and communicative model of decision support environments, we present an abstract

Cloud computing relies on the collection and distribution of services from internet-based data centers. With the large resource pool available in internet wide range of users are accessing the cloud. Load balance is important feature involving resource allocation to prevent overloading of any system or optimal use of resources. Major load in cloud network are concerned with CPU, memory and network. This cloud computing aspect has not yet earned too much coverage. Although load balancing is an important feature for cloud computing, concurrent computing etc. In these areas, several algorithms were suggested to solve load balance problem. However, it does recommend very few cloud computing algorithms. Given that cloud storage differs considerably from all other environments, particular load balancing algorithm should will built in sort to serve its needs. This work proposes novel load-balancing algorithm based on artificial bee colony algorithm and load balancing min-min scheduling algorithm for balancing load in cloud computing network. Simulation here is carried out in clouds to generate comparative results. Improving on various parameters like power consumption, resource utilization, stability of system are some major areas focused on. This work has used algorithm that has the best efficiency of resources, optimal performance, minimal response time, scalability and durability in integrated resource planning.

Functionality of electronic commerce enabling technologies is dependent upon pervasive networks that a large number of applications share. Given the scarcity of network resources, it is imperative to allocate existing resources based on the actual needs of its users. In this paper, we study a two sided matching algorithm that enables such an allocation using tools from matching literature. Network system deploys intelligent agents that negotiate terms of allocation assignments with other intelligent agents that represent the users. We report the time complexity of the algorithm and give an example on how the mechanism performs.

In this paper, we present a complete view of an agentoriented software engineering methodology called ASEM E (for AgentSystemsEngineeringM Ethodology). Several parts of the methodology concerning different aspects of the whole development process have been already published in the past in several papers. However, our goal in this paper is to provide a global view on the methodology by providing information about the agent (and multi-agent systems) development process along with recent works concerning the tools that we have developed in order to facilitate the use of ASEM E by agent systems developers. We also provide some information on the different practical applications that we have developed by using ASEM E and which prove that ASEM E is very well suited for an easy development or real world applications.

Nowadays, worldwide public utility services providers feel the necessity of new flexible and scalable solutions aimed at managing their distribution networks and services. This is fundamentally due to the continuously technological evolution of distribution network infrastructures that impacts deeply on the software in charge of handling the services supply chain management. The purpose of this paper is to present an innovative system aimed at defining a new approach to resource inventory. This approach is designed both to reduce the influence of infrastructure evolution and to enable value-added services performed by autonomous intelligent agents. Based on the integration of semantic web technologies and agents paradigm, the system's mission is to define a new ontology-based model for resource inventory. Moreover, the system defines a new behavioral model enabling software agents to effectively react to the network environment in which they are embedded.

This paper discusses the design and the development of an original information system based on intelligent agent technologies and dedicated to forest fire prevention and fighting. It describes the work to be carried out in order to achieve and formalise knowledge in the field of forest fires. It presents a detailed demonstration built around two realistic scenarios, where several actors and software were implicated. #

Military strategies will shortly make intensive use of autonomous systems while the Internet of Battle Things (IoBT) will grow military systems’ complexity to new heights. The cyber defense of the battlespace will then become arduous for humans, if not impossible, due to disconnections, the difficulty of supervising masses of interconnected devices, and the scarcity of cyber defense competences on the battleground. An autonomous intelligent cyber defense of the battlefield becomes necessary in such a context. In response to such needs, this chapter presents and illustrates the rationale, concept and future research directions of (Multiple) Autonomous Intelligent Cyber defense Agents, (M)AICA, and NATO’s initial AICA Reference Architecture, AICARA.

Applications of artificial intelligence in cyber warfare have been mainly postulated and studied in the context of defensive operations. This paper provides an introductory overview of the use of autonomous agents in offensive cyber warfare, drawing on available open literature. The study supplies an introduction to the taxonomy and science underlying intelligent agents and their strengths and weaknesses: the technological elements that autonomous agents should include are explained, as well as the economics involved. The paper also aims to explore possible legal implications of the use of autonomous agents and shows how they could fit into the legal context of warfare. The conclusion of the study is that the use of AI technologies will be an important part of cyber offensive operations, from both the technological and the economical aspects; however, the legal and doctrinal landscape is still uncertain and proper frameworks are still to be developed.

In this paper, we propose an intelligent and secure internet of things approach for the healthcare system that monitors the patient heart rate in real-time and from any place. Thanks to the agent, the proposed system can predict the critical condition before it even happens and takes fast and apt decisions in an emergency case. Based on the experimentation, the proposed system is convenient, reliable, and ensures data security at a low cost. The proposed algorithm outperforms other algorithms regarding the system's operational efficiency. It is more suitable for devices with power, storage, and processing limitations, such as in IoT devices. Also, agents are the better current technologies for heterogeneous and distributed systems, such as the internet of things. Moreover, this approach's scalability makes it suitable for a broad range of IoT environments, including smart homes, smart cities, dynamic and large-area networks, etc.

In recent years, the Internet of Things (IoT) has become well known. It has
attracted much attention thanks to its powerful application in different fields. Currently, billions of IoT devices are connected. The massive rise in the number of connected devices instantly produces further data that requires high storage and processing technology. Besides, the IoT equipment has limited processing, and storage capability did not allow data processing or even storage. Also, things cannot make smart and quick decisions to achieve their goals, and the thing ability to communicate with other things depends on service similarity and communication protocols; this will impact the performance, efficiency, development, and scalability of IoT applications. This thesis provides three main contributions, in the first contribution, we propose a Cloud-IoT approach to provide an efficient solution for the storage and analysis of data generated by IoT applications and improve IoT scalability. In order to demonstrate the viability of the proposed approach, a Cloud-IoT system for remote patient monitoring is developed.
IoT security becomes a more challenging problem due to the computing and communication limits of IoT devices make IoT more vulnerable to security and privacy attacks. Hence, as a second contribution, we propose a robust solution based on lightweight cryptography to ensure data security. Also, we have used the access control mechanism to ensure data privacy. The experimentation demonstrates that the proposed solution more suitable for IoT devices. To tap the most out of massive data streams, IoT needs real-time management and analysis of data. In order to enhance the intelligence of IoT devices and to improve our first approach, we have developed an efficient, autonomous, and real-time solution based on the agent for data management and analysis as a third contribution. The proposed system can make fast and apt decisions in an emergency case.

The concept of knowledge management is not new in information systems practice and research. However, radical changes in the business environment have suggested limitations of the traditional information-processing view of knowledge management. Specifically, it is being realized that the programmed nature of heuristics underlying such systems may be inadequate for coping with the demands imposed by the new business environments. New business environments are characterized not only by rapid pace of change, but also discontinuous nature of such change. The new business environment, characterized by dynamically discontinuous change, requires a re-conceptualization of knowledge management as it has been understood in information systems practice and research. One such conceptualization is proposed in the form of a sense-making model of knowledge management for new business environments. Application of this framework will facilitate business model innovation necessary for sustainable competitive advantage in the new business environment characterized by dynamic, discontinuous and radical pace of change.

In this paper, we propose a novel, secure, and intelligent IoT approach based on agent, we have implemented in the health care domain, where we developed an intelligent patient monitoring system for monitoring the patients heart rate automatically. Our system is more intelligent that can anticipate the critical condition before it even happens, send a message to the patient family, doctors, nurses, as well as hospital in-charge personal, and launch an alarm to be assisted by the nearest people in place. Also, our architecture ensures the authentication, authorization, and data sensing confidentiality. Hospitals and medical clinics can utilize our system to monitor their outpatients who are in danger of unpredictable health conditions. The approach presented in the paper can also be applied to other IoT domains.

Information systems with an "intelligent" or "knowledge" component are now prevalent and include knowledge-based systems, decision support systems, intelligent agents, and knowledge management systems. These systems are in principle capable of explaining their reasoning or justifying their behavior. There appears to be a lack of understanding, however, of the benefits that can flow from explanation use, and how an explanation function should be constructed.

E-government is gaining momentum and has firmly established itself in addition to common terms such as 'e-commerce' or 'e-business'. Given that e-government services extend across different organisational boundaries and heterogeneous infrastructures, there is a critical need to manage the knowledge and information resources stored in these disparate systems. Semantic Web technologies have the potential to manage the knowledge and coordinate Government-to-Government (G2G) processes. Based on the foundations of Semantic Web, including ontologies, knowledge representation, multi-agent systems and web services; Knowledge Management (KM) and G2G processes, we present a vision for KM for G2G process coordination. The Semantic G2G integration can support the transparent flow of semantically enriched information and knowledge, including content and know-how and enable collaborative G2G processes within and across governmental agencies.

The last decades, advances in information technologies and increased competition have changed the business environment in the food and beverages industry, particularly in the European Union, which is characterised by the proliferation of small and medium enterprises. Many food companies are now aggressively focusing on logistics management as the last frontier to gain and sustain a competitive advantage.This study describes a model of intelligent food supply chain that improves efficiency within the supply chain. The aim of the paper is to demonstrate that agent technology can optimise food supply chains by (a) reviewing intelligent agents applications for supply chain optimisation and (b) illustrating how a multi-agent system can optimise performance of a beverage logistics network. Firstly, we review and synthesise existing applications in comparison to traditional and Internet-based technologies and critically evaluate agent technology applicability for supply chain management. We model the beer supply network to demonstrate that products can acquire intelligence to direct themselves throughout the distribution network. Optimisation agents can help solve specific problems of beverage supply: reduce inventories and lessen bullwhip effect, improve communication, and enable chain coordination without adverse risk sharing. Further, they gain a capability to be purchased and sold while in transit.Overviews of the supporting technologies that make such a supply chain a reality are fully discussed. In particular, optimisation agents have the characteristics of autonomous action, being proactive, reactive, and able to communicate. We demonstrate that agents enhance the flexibility, information visibility, and efficiency of the supply chain management. Suggestions and recommendations for further research are provided. Simulations of the agent-enabled supply optimisation can be used to benchmark for future research and development associated with building an optimisation agent.

The vast amount of heterogeneous information sources available on the Internet demands advanced solutions for acquiring, mediating, and maintaining relevant information for the common user. Intelligent information agents are autonomous computational software entities that are especially meant to (1) provide pro-active resource discovery, (2) resolve information impedance of information consumers and providers, and (3) offer value-added information services and products. These agents are supposed to cope with the difficulties associated with the information overload of the user, preferably just in time.Based on a systematic classification of intelligent information agents, this paper presents an overview of the basic key enabling technologies needed to build such agents, and respective examples of information agent systems currently deployed on the Internet.

The problem of energy conservation in buildings is a multidimensional one. Researchers from a variety of disciplines have been working on this problem. It remains a challenging and yet rewarding study. In the past three decades, a plethora of scientific and technological publications on energy conservation in buildings have been presented in international journals. In this work, we discuss the potentiality of artificial intelligence (AI) as a design tool in building an automation system. The application of contemporary AI techniques creates intelligent buildings with the following main goals: energy efficiency, comfort, health and productivity in living spaces. Two modern domains of AI that are widely used in buildings are computational intelligence (CI) or soft computing and distributed artificial intelligence (DAI). DAI includes intelligent agents (IAs), multiagent systems (MASs) and ambient intelligence. However, there is a lack of systematic review of research efforts and achievements mainly on IA and MAS domains. This chapter briefly presents expert systems and CI techniques and outlines how they operate. The major objective of this chapter is to illustrate how IAs and MASs may play an important role in conserving energy in buildings.

Automated Identification and in particular, Radio Frequency Identification (RFID) promises to assist with the automation of mass customised production processes by simplifying the retrieval, tracking and usage of highly specialised components.

The term ‘posthumanism’ has been employed to describe a diverse array of phenomena ranging from academic disciplines and artistic movements to political advocacy campaigns and the development of commercial technologies. Such phenomena differ widely in their subject matter, purpose, and methodology, raising the question of whether it is possible to fashion a coherent definition of posthumanism that encompasses all phenomena thus labelled. In this text, we seek to bring greater clarity to this discussion by formulating a novel conceptual framework for classifying existing and potential forms of posthumanism. The framework asserts that a given form of posthumanism can be classified: 1) either as an analytic posthumanism that understands ‘posthumanity’ as a sociotechnological reality that already exists in the contemporary world or as a synthetic posthumanism that understands ‘posthumanity’ as a collection of hypothetical future entities whose development can be intentionally realized or prevented; and 2) either as a theoretical posthumanism that primarily seeks to develop new knowledge or as a practical posthumanism that seeks to bring about some social, political, economic, or technological change. By arranging these two characteristics as orthogonal axes, we obtain a matrix that categorizes a form of posthumanism into one of four quadrants or as a hybrid posthumanism spanning all quadrants. It is suggested that the five resulting types can be understood roughly as posthumanisms of critique, imagination, conversion, control, and production.
We then employ this framework to classify a wide variety of posthumanisms, such as critical, cultural, philosophical, sociopolitical, and popular (or ‘commercial’) posthumanism; science fiction; techno-idealism; metahumanism; neohumanism; antihumanism; prehumanism; feminist new materialism; the posthumanities; biopolitical posthumanism, including bioconservatism and transhumanism (with specialized objective and instrumental typologies offered for classifying forms of transhumanism); and organizational posthumanism. Of particular interest for our research is the classification of organizational posthumanism as a hybrid posthumanism combining analytic, synthetic, theoretical, and practical aspects. We argue that the framework proposed in this text generates a typology that is flexible enough to encompass the full range of posthumanisms while being discriminating enough to order posthumanisms into types that reveal new insights about their nature and dynamics.

Key organizational decisions made by sapient AIs. The pressure to undergo neuroprosthetic augmentation in order to compete with genetically enhanced coworkers. A corporate headquarters that exists only in cyberspace as a persistent virtual world. A project team whose members interact socially as online avatars without knowing or caring whether fellow team members are human beings or robots.
Futurologists’ visions of the dawning age of ‘posthumanized’ organizations range from the disquieting to the exhilarating. Which of these visions are compatible with our best current understanding of the capacities and the limits of human intelligence, physiology, and sociality? And what can posthumanist thought reveal about the forces of technologization that are transforming how we collaborate with one another – and with ever more sophisticated artificial agents and systems – to achieve shared goals?
This book develops new insights into the evolving nature of intelligent agency and collaboration by applying the post-anthropocentric and post-dualistic methodologies of posthumanism to the fields of organizational theory and management. Building on a comprehensive typology of posthumanism, an emerging ‘organizational posthumanism’ is described which makes sense of the dynamics of technological posthumanization that are reshaping the members, personnel structures, information systems, processes, physical and virtual spaces, and external environments available to organizations. Conceptual frameworks and analytical tools are formulated for use in diagnosing and guiding the ongoing convergence in the capacities of human and artificial actors that is being spurred by novel technologies relating to human augmentation, synthetic agency, and digital-physical ecosystems. As the first systematic investigation of these topics, this text will be of interest to scholars and students of posthumanism and management and to management practitioners who must grapple on a daily basis with the forces of technologization that are increasingly powerful drivers of organizational change.

Building on existing forms of critical, cultural, biopolitical, and sociopolitical posthumanism, in this text a new framework is developed for understanding and guiding the forces of technologization and posthumanization that are reshaping contemporary organizations. This ‘organizational posthumanism’ is an approach to analyzing, creating, and managing organizations that employs a post-dualistic and post-anthropocentric perspective and which recognizes that emerging technologies will increasingly transform the kinds of members, structures, systems, processes, physical and virtual spaces, and external ecosystems that are available for organizations to utilize. It is argued that this posthumanizing technologization of organizations will especially be driven by developments in three areas: 1) technologies for human augmentation and enhancement, including many forms of neuroprosthetics and genetic engineering; 2) technologies for synthetic agency, including robotics, artificial intelligence, and artificial life; and 3) technologies for digital-physical ecosystems and networks that create the environments within which and infrastructure through which human and artificial agents will interact.
Drawing on a typology of contemporary posthumanism, organizational posthumanism is shown to be a hybrid form of posthumanism that combines both analytic, synthetic, theoretical, and practical elements. Like analytic forms of posthumanism, organizational posthumanism recognizes the extent to which posthumanization has already transformed businesses and other organizations; it thus occupies itself with understanding organizations as they exist today and developing strategies and best practices for responding to the forces of posthumanization. On the other hand, like synthetic forms of posthumanism, organizational posthumanism anticipates the fact that intensifying and accelerating processes of posthumanization will create future realities quite different from those seen today; it thus attempts to develop conceptual schemas to account for such potential developments, both as a means of expanding our theoretical knowledge of organizations and of enhancing the ability of contemporary organizational stakeholders to conduct strategic planning for a radically posthumanized long-term future.

In this text we present the Posthuman Management Matrix, a model for understanding the ways in which organizations of the future will be affected by the blurring – or even dissolution – of boundaries between human beings and computers. In this model, an organization’s employees and consumers can include two different kinds of agents (human and artificial) who may possess either of two sets of characteristics (anthropic or computer-like); the model thus defines four types of possible entities. For millennia, the only type of relevance for management theory and practice was that of human agents who possess anthropic characteristics – i.e., ‘natural human beings.’ During the 20th Century, the arrival of computers and industrial robots made relevant a second type: that of artificial agents possessing computer-like characteristics.
Management theory and practice have traditionally overlooked the remaining two types of possible entities – human agents possessing computer-like physical and cognitive characteristics (which can be referred to as ‘cyborgs’) and artificial agents possessing anthropic physical and cognitive characteristics (which for lack of a more appropriate term might be called ‘bioroids’) – because such agents did not yet exist to serve as employees or consumers for organizations. However, in this text we argue that ongoing developments in neuroprosthetics, genetic engineering, virtual reality, robotics, and artificial intelligence are indeed giving rise to such types of agents and that new spheres of management theory and practice will be needed to allow organizations to understand the operational, legal, and ethical issues that arise as their pools of potential workers and customers evolve to include human beings whose bodies and minds incorporate ever more computerized elements and artificial entities that increasingly resemble biological beings.
By analyzing the full spectrum of human, computerized, and hybrid entities that will constitute future organizations, the Posthuman Management Matrix highlights ways in which established disciplines such as cybernetics, systems theory, organizational design, and enterprise architecture can work alongside new disciplines like psychological engineering, AI resource management, metapsychology, and exoeconomics to help organizations anticipate and adapt to posthumanizing technological and social change.

This thesis concerns the making and performing of music with new digital musical instruments (DMIs) designed for ensemble performance. While computer music has advanced to the point where a huge variety of digital instruments are common in educational, recreational, and professional music-making, these instruments rarely seek to enhance the ensemble context in which they are used. Interaction models that map individual gestures to sound have been previously studied, but the interactions of ensembles within these models are not well understood. In this research, new ensemble-focussed instruments have been designed and deployed in an ongoing artistic practice. These instruments have also been evaluated to find out whether, and if so how, they affect the ensembles and music that is made with them.

Throughout this thesis, six ensemble-focussed DMIs are introduced for mobile touch-screen computers. A series of improvised rehearsals and performances leads to the identification of a vocabulary of continuous performative touch-gestures and a system for tracking these collaborative performances in real time using tools from machine learning. The tracking system is posed as an intelligent agent that can continually analyse the gestural states of performers, and trigger a response in the performers' user interfaces at appropriate moments. The hypothesis is that the agent interaction and UI response can enhance improvised performances, allowing performers to better explore creative interactions with each other, produce better music, and have a more enjoyable experience.

Two formal studies are described where participants rate their perceptions of improvised performances with a variety of designs for agent-app interaction. The first, with three expert performers, informed refinements for a set of apps. The most successful interface was redesigned and investigated further in a second study with 16 non-expert participants. In the final interface, each performer freely improvised with a limited number of notes; at moments of peak gestural change, the agent presented users with the opportunity to try different notes. This interface is shown to produce performances that are longer, as well as demonstrate improved perceptions of musical structure, group interaction, enjoyment and overall quality.

Overall, this research examined ensemble DMI performance in unprecedented scope and detail, with more than 150 interaction sessions recorded. Informed by the results of lab and field studies using quantitative and qualitative methods, four generations of ensemble-focussed interface have been developed and refined. The results of the most recent studies assure us that the intelligent agent interaction does enhance improvised performances.

This article is a study of St. Thomas Aquinas’ De principiis naturae 3. Firstly, matter, form, and matter are not enough to explain the generations: another principle is required, which operates the generation. This is the efficient cause, which does not operate if it is not moved by an end. Acting for an end is proper both to voluntary and to natural agents. He proves this by means of a complex conditional hypothetic syllogism. Then, he distinguishes the senses of cause and principle: a cause is that, from the being of which another thing follows; a principle is simply what is prior to another thing. Lastly, he distinguishes the element’s notion from the one of prime matter. Based on this, we may establish a generic notion of matter, the principal species of which would be the prime matter, the subject and the element.

Web Services enable computers to interact and exploit Web-accessible programs without human intervention. Despite researchers agree that mobile agent technology will obtain significant benefits from this line of research, the lack of proper development tools hinder the widespread adoption of mobile agent technology on the Web. This paper describes a novel programming language called WS-Log whose goal is to provide a tight integration between mobile agents and Web Services. Examples and experimental results showing some of the advantages of WS-Log are also reported.

After having illustrated in the previous chapters the main features of my cognitive-epistemological analysis of abduction, it is necessary to further stress the dynamics involved in the interplay between internal and external representations in the case of logic. This will provide a tool for exploring the relationship between human and logical agents in section 7.1. First of all I will further develop my distinction between creative and mimetic artifacts. As I explained in chapter three these artifacts play the role of external objects (representations) active in what I have called disembodiment of mind. Mimetic external representations mirror concepts and problems that are already represented in the brain and need to be enhanced, solved, further complicated, etc. so they can sometimes creatively give rise to new concepts and meanings. From this perspective the expansion of the minds is, in the meantime, a continuous process of disembodiment of the minds themselves into the material world around them so that the evolution of the mind is inextricably linked with the evolution of many kinds of large, integrated, material cognitive systems. This chapter illustrates some features of this extraordinary interplay by focusing on the construction of logical cognitive systems and its consequences for abductive reasoning.

Knowledge Management is the process of collecting information which supports to create disseminate and utilize the knowledge between the individuals, groups within an organization or independent organization. The process of knowledge management involves various steps such as identifying, collecting, storing, sharing, applying, creating and selling knowledge. Agents are autonomous intelligent computer programs that perform tasks on behalf of the user or user-initiated process by using its knowledge base. Agents are designed and developed in such a way that they are goal-oriented, adaptive, reactive and mobile. Agents incorporated in the process of knowledge management should be capable of communicating with other agents by using its common characteristics namely cooperate, coordinate and collaborate. These common characteristics will improve the performance of knowledge management process by helping the agents to discover the knowledge from it. Agent uses its learning characteristics to update its knowledge base whenever it encounters new information from the organization. Agent’s uses its dynamic characteristics for knowledge sharing among users in an organization. Knowledge sharing is done both at work group and at company level. During this process agent roles associated with the knowledge management and knowledge discovery are identified. This paper aims at describing such agents and their roles.

Seven multi-searcher agents —Copernic, EZSearch, MataHari, iMine, WebSeeker, WebFerret and WebStorm— are compared measuring precision, recall and response time on the first twenty results returned for fifteen queries. All search engines were done on August 21th, 1999. Acomparative study of the two top agents of this paper with HotBot and AltaVista shows the advantages of the intelligent agents multi-seacher in relationshipwith the current search engines

Contracts are designed to govern the relations between business partners and allocate risk among them, yet they cannot mitigate all risks; hence, dispute resolution mechanisms have been developed to assist. According to research, arbitration is considered one of the most efficient legally binding dispute resolution mechanisms. Since initiating an arbitration case against business partners often severs the business relationship between them, predicting the arbitrator's decision becomes valuable to the arbitrating parties. To do so, arbitration prediction models are suggested in this paper through modeling the arbitrator's award in two stages: evidence admissibility and evidence evaluation. While arbitrators currently admit evidence in a relatively unsystematic way, this proposed admissibility framework systemizes the current practice by preserving its subjectivity, yet aligning it with the widely deployed rules of arbitration. This research further proposes an evidence evaluation model, providing a rapid answer to the famous commercial arbitration battle, discovery. While the current arbitrators' practice in allowing discovery is not systematic, the proposed optimization model is a tool that could systematically assist arbitrators trading between the arbitration key characteristic, efficiency, and justice. This is achieved by assigning weights to evidence parameters such as sufficiency and credibility, which in turn provide numerical measures to reduce the decision's subjectivity.

Cognitive architectures play a vital role in providing blueprints for building future intelligent systems supporting a broad range of capabilities similar to those of humans. How useful are existing architectures for creating artificial general intelligence? A critical survey of the state of the art in cognitive architectures is presented providing a useful insight into the possible frameworks for general intelligence. Grand challenges and an outline of the most promising future directions are described. : "W. Duch".

System-based decision-making functionality has matured over the last decade due to the constant evolution of technological decision execution capabilities. Intelligent agents, cyber-physical systems employing automated and autonomous mechanisms and components, and recent breakthroughs of household robotics require standardized and formalized automated decision making (DM) process design. Employing an integrated systems thinking approach, we propose a model-based approach which integrates decision-support and decision-making mechanisms into system models. Our formal conceptual metamodel streamlines a standard, generic DM process, enabling the coordination and consolidation of local system-based decisions in a loosely coordinated system-of-systems or a complex system of autonomous agents into a coherent, environment-aware global decision. Our framework utilizes Object Process Methodology -OPMa robust conceptual modeling framework for complex system and process modeling and design.

The target article by Franklin, Strain, McCall, and Baars (2013) provides a useful way forward in achieving the goals of artificial general intelligence (AGI). They explicate the conceptual commitments of the Learning Intelligent Distribution Agent (LIDA) model through specification of the importance of each  commitment, not only to this model, but also to the goal of AGI. Proponents of other cognitive architectures should engage in similar efforts to collaboratively approach the goal of AGI. While we view the overall LIDA approach as beneficial, and commend the authors for their extensive interdisciplinary grounding of the model in experimental psychology, cognitive neuroscience and artificial intelligence, we raise a set of inter-related issues concerning what else, from our perspective, might be necessary to achieve AGI. Therefore, the aim of our commentary is to constructively highlight and expand these ideas. Our focus is on the role of embodiment for learning and for social interaction and how these factors may help to improve the LIDA model, and AGI architectures, more generally.

Two modes of matching people with jobs prevail at present: 1) hierarchical planning and 2) distributed markets. Each has strengths and limitations, but few systems have been designed to take advantage of strengths corresponding to both. With evolving information technology, however, the job-matching process could be accomplished far more equitably and efficiently using web-based markets within the firm, and intelligent agents offer excellent potential to help both potential employees and employers find one another in a distributed, electronic marketplace. But realizing this potential goes well beyond simply changing the rules of internal job matching or making agent technology available to job searchers. Rather, the corresponding markets and technologies must be designed, together, to mutually accomplish the desired results (e.g., efficient and effective matching) and conform to necessary properties (e.g., market clearing). Through the research described in this paper, we draw from Game Theory results to assess the feasibility of using two-sided matching algorithms to address this market-design problem. We also draw from current agent research to address the information technology dimension of the problem by implementing a proof-of-concept multi-agent system to enact, automate and support the corresponding market solution. This paper integrates the key economic and technological elements required to design robust electronic employment markets. And the corresponding research provides new knowledge and insight into co-development of the requisite economic markets and agent technologies.