On core stability and extendability

This paper investigates conditions under which the core of a TU cooperative game is stable. In particular the author extends the idea of extendability to find new conditions under which the core is stable. It is also shown that these new conditions are not necessary for core stability.core stability, stable core, extendability

Characterizing core stability with fuzzy games

This paper investigates core stability of cooperative, TU games via a fuzzy extension of the totally balanced cover of a TU game. The stability of the core of the fuzzy extension of a game, the concave extension, is shown to reflect the core stability of the original game and vice versa. Stability of the core is then shown to be equivalent to the existence of an equilibrium of a certain correspondence.cooperative game, core, stable set, fuzzy coalition, fuzzy game, core stability

Universal characterization sets for the nucleolus in balanced games

We provide a new mo dus op erandi for the computation of the nucleolus in co op- erative games with transferable utility. Using the concept of dual game we extend the theory of characterization sets. Dually essential and dually saturated coalitions determine b oth the core and the nucleolus in monotonic games whenever the core is non-empty. We show how these two sets are related with the existing charac- terization sets. In particular we prove that if the grand coalition is vital then the intersection of essential and dually essential coalitions forms a characterization set itself. We conclude with a sample computation of the nucleolus of bankruptcy games - the shortest of its kind

Proceedings of the 2nd International Workshop on Security in Mobile Multiagent Systems

This report contains the Proceedings of the Second Workshop on Security on Security of Mobile Multiagent Systems (SEMAS2002). The Workshop was held in Montreal, Canada as a satellite event to the 5th International Conference on Autonomous Agents in 2001. The far reaching influence of the Internet has resulted in an increased interest in agent technologies, which are poised to play a key role in the implementation of successful Internet and WWW-based applications in the future. While there is still considerable hype concerning agent technologies, there is also an increasing awareness of the problems involved. In particular, that these applications will not be successful unless security issues can be adequately handled. Although there is a large body of work on cryptographic techniques that provide basic building-blocks to solve specific security problems, relatively little work has been done in investigating security in the multiagent system context. Related problems are secure communication between agents, implementation of trust models/authentication procedures or even reflections of agents on security mechanisms. The introduction of mobile software agents significantly increases the risks involved in Internet and WWW-based applications. For example, if we allow agents to enter our hosts or private networks, we must offer the agents a platform so that they can execute correctly but at the same time ensure that they will not have deleterious effects on our hosts or any other agents / processes in our network. If we send out mobile agents, we should also be able to provide guarantees about specific aspects of their behaviour, i.e., we are not only interested in whether the agents carry out-out their intended task correctly. They must defend themselves against attacks initiated by other agents, and survive in potentially malicious environments. Agent technologies can also be used to support network security. For example in the context of intrusion detection, intelligent guardian agents may be used to analyse the behaviour of agents on a firewall or intelligent monitoring agents can be used to analyse the behaviour of agents migrating through a network. Part of the inspiration for such multi-agent systems comes from primitive animal behaviour, such as that of guardian ants protecting their hill or from biological immune systems

Constrained Rationality: Formal Value-Driven Enterprise Knowledge Management Modelling and Analysis Framework for Strategic Business, Technology and Public Policy Decision Making & Conflict Resolution

The complexity of the strategic decision making environments, in which busi- nesses and governments live in, makes such decisions more and more difficult to make. People and organizations with access to the best known decision support modelling and analysis tools and methods cannot seem to benefit from such re- sources. We argue that the reason behind the failure of most current decision and game theoretic methods is that these methods are made to deal with operational and tactical decisions, not strategic decisions. While operational and tactical decisions are clear and concise with limited scope and short-term implications, allowing them to be easily formalized and reasoned about, strategic decisions tend to be more gen- eral, ill-structured, complex, with broader scope and long-term implications. This research work starts with a review of the current dominant modelling and analysis approaches, their strengths and shortcomings, and a look at how pioneers in the field criticize these approaches as restrictive and unpractical. Then, the work goes on to propose a new paradigm shift in how strategic decisions and conflicts should be modelled and analyzed. Constrained Rationality is a formal qualitative framework, with a robust method- ological approach, to model and analyze ill-structured strategic single and multi- agent decision making situations and conflicts. The framework brings back the strategic decision making problem to its roots, from being an optimization/efficiency problem about evaluating predetermined alternatives to satisfy predetermined pref- erences or utility functions, as most current decision and game theoretic approaches treats it, to being an effectiveness problem of: 1) identifying and modelling explic- itly the strategic and conflicting goals of the involved agents (also called players and decision makers in our work), and the decision making context (the external and internal constraints including the agents priorities, emotions and attitudes); 2) finding, uncovering and/or creating the right set of alternatives to consider; and then 3) reasoning about the ability of each of these alternatives to satisfy the stated strategic goals the agents have, given their constraints. Instead of assuming that the agents’ alternatives and preferences are well-known, as most current decision and game theoretic approaches do, the Constrained Rationality framework start by capturing and modelling clearly the context of the strategic decision making situation, and then use this contextual knowledge to guide the process of finding the agents’ alternatives, analyzing them, and choosing the most effective one. The Constrained Rationality framework, at its heart, provides a novel set of modelling facilities to capture the contextual knowledge of the decision making sit- uations. These modelling facilities are based on the Viewpoint-based Value-Driven - Enterprise Knowledge Management (ViVD-EKM) conceptual modelling frame- work proposed by Al-Shawa (2006b), and include facilities: to capture and model the goals and constraints of the different involved agents, in the decision making situation, in complex graphs within viewpoint models; and to model the complex cause-effect interrelationships among theses goals and constraints. The framework provides a set of robust, extensible and formal Goal-to-Goal and Constraint-to Goal relationships, through which qualitative linguistic value labels about the goals’ op- erationalization, achievement and prevention propagate these relationships until they are finalized to reflect the state of the goals’ achievement at any single point of time during the situation. The framework provides also sufficient, but extensible, representation facilities to model the agents’ priorities, emotional valences and attitudes as value properties with qualitative linguistic value labels. All of these goals and constraints, and the value labels of their respective value properties (operationalization, achievement, prevention, importance, emotional valence, etc.) are used to evaluate the different alternatives (options, plans, products, product/design features, etc.) agents have, and generate cardinal and ordinal preferences for the agents over their respective alternatives. For analysts, and decision makers alike, these preferences can easily be verified, validates and traced back to how much each of these alternatives con- tribute to each agent’s strategic goals, given his constraints, priorities, emotions and attitudes. The Constrained Rationality framework offers a detailed process to model and analyze decision making situations, with special paths and steps to satisfy the spe- cific needs of: 1) single-agent decision making situations, or multi-agent situations in which agents act in an individualistic manner with no regard to others’ current or future options and decisions; 2) collaborative multi-agent decision making situ- ations, where agents disclose their goals and constraints, and choose from a set of shared alternatives one that best satisfy the collective goals of the group; and 3) adversarial competitive multi-agent decision making situations (called Games, in gamete theory literature, or Conflicts, in the broader management science litera- ture). The framework’s modelling and analysis process covers also three types of con- flicts/games: a) non-cooperative games, where agents can take unilateral moves among the game’s states; b) cooperative games, with no coalitions allowed, where agents still act individually (not as groups/coalitions) taking both unilateral moves and cooperative single-step moves when it benefit them; and c) cooperative games, with coalitions allowed, where the games include, in addition to individual agents, agents who are grouped in formal alliances/coalitions, giving themselves the ability to take multi-step group moves to advance their collective position in the game. ...

Ostinato Process Model for Visual Network Analytics: Experiments in Innovation Ecosystems

More often than ever before, innovation activities are crossing organizational boundaries and taking place in the spaces between formal, organizational structures. This new context for innovation activities is increasingly referred to as an innovation ecosystem. Open innovation, co-creation, user-driven innovation, API and platform economies, and business ecosystems are key drivers of the transformation. Innovation ecosystems are open, dynamic systems that cross geographical as well as organizational boundaries and include financial, technological, and political dimensions. Talented humans have a crucial driving role in ecosystemic innovation activities. Innovation ecosystems set a new framework for analyzing, investigating, and therefore measuring innovation.Measuring and visualizing innovation is difficult, particularly within innovation ecosystems where activities take very complex forms and even identifying all relevant actors and stakeholders is challenging. At the same time, ecosystem-level analyses of innovation ecosystem structures are imperative for three groups: innovation ecosystem scholars, policy and decision makers, and innovation ecosystem actors. Moreover, new sources of digital data on innovation activities have become available, introducing new opportunities to investigate innovation ecosystems at the ecosystem level.In this dissertation, we seek to develop new means to utilize digital data in analyzing innovation ecosystems at the ecosystem level. We take an action design research approach to develop the means to investigate the structural properties of innovation ecosystems at the ecosystem level by using visual network analytics. We start from the realization that interconnectedness is a key property of innovation ecosystems. Addressing innovation ecosystems as networks, that is, as collections of pairs of interconnected innovation ecosystem actors, allows scholars and practitioners to gain insight into innovation ecosystem structures and the structural roles of individual ecosystem actors. To determine how innovation ecosystems should be modeled and analyzed as networks, we investigate several innovation ecosystems representing regional, metropolitan, national, and international contexts as well as investigating the context of programmatic activities that support innovation and growth. Our main objective in the dissertation is to develop a process model for data-driven visual network analytics of innovation ecosystems.Visual network analytics is a valuable method for investigating and mapping the innovation ecosystem structure. In the proposed approach, transactional microdata on innovation ecosystem actors and their interconnections is collected from various digital sources. Innovation ecosystem actors are represented as network nodes that are connected through transactions, including investments and acquisitions and advisory, founder, and contributor affiliations. Network metrics are used to quantify actors’ structural positions. Interactive visual analytics tools are used to support the visual exploration of the innovation ecosystem under investigation by using both top-down and bottom-up strategies.This work makes several contributions to the art and science of data-driven visual network analytics of innovation ecosystems. Most importantly, the dissertation proposes the ostinato model, an iterative, user-centric, process-automated model for data-driven visual network analytics. The ostinato model simultaneously supports the automation of the process and enables interactive and transparent exploration. The model has two phases: data collection and refinement, and network creation and analysis. The data collection and refinement phase is further divided into entity index creation, Web/API crawling, scraping, and data aggregation. The network construction and analysis phase is composed of filtering in entities, node and edge creation, metrics calculation, node and edge filtering, entity index refinement, layout processing, and visual properties configuration. The cycle of exploration and automation characterizes the model and is embedded in each phase.In addition to the ostinato model, we contribute a set of design guidelines for modeling and visualizing innovation ecosystems as networks. Finally, we contribute to the empirical body of knowledge on innovation ecosystems through a series of investigations of innovation ecosystems of different levels of abstraction and complexity. Innovation ecosystem scholars, policy makers, orchestrators, and other stakeholders in the innovation ecosystem under investigation in this dissertation have subscribed to the approach presented herein. The design guidelines, together with the ostinato model, allow innovation ecosystem investigators and actors an opportunity to significantly advance in utilizing visual network analytics in managing and orchestrating innovation ecosystems. Further research and development of supporting processes and tools are needed to take full advantage of the presented approach in analyzing, investigating, facilitating, and orchestrating interorganizational innovation activities