The relationship between equilibrium convergence to a uniform quality distribution and price is investigated in the Q-model, a self-organizing, evolutionary computational matching model of a fixed-price post-secondary higher education created by Ortmann and Slobodyan (2006). The Q-model is replicated with price equaling 100% its Ortmann and Slobodyan (2006) value, Varying the fixed price between 0% and 200% reveals thresholds at which the Q-model reaches different market clustering configurations. Results indicate structural market robustness to prices less than 100% and high sensitivity to prices greater than 100%.

An understanding of the policy and resource availability constraints under which others operate is important for effectively developing and resourcing plans in a multi-agent context. Such constraints (or norms) are not necessarily public knowledge, even within a team of collaborating agents. What is required are mechanisms to enable agents to keep track of who might have and be willing to provide the resources required for enacting a plan by modeling the policies of others regarding resource use, information provision, etc. We propose a technique that combines machine learning and argumentation for identifying and modeling the policies of others. Furthermore, we demonstrate the utility of this novel combination of techniques through empirical evaluation.

PMRFSim is a proof of concept geospatial social agent-based simulation capable of examining the interactions of 60,000+ agents over a simulated year within a few minutes. PMRFSim utilizes real world data from sources ranging from the U.S. Census Bureau, a regional sociologist, and base security. PMRFSim models two types of agents, normal and adverse agents. Adverse agents have harmful intent and goals to spread negative sentiment and acquire intelligence. All agents are endowed with demographic and geospatial attributes. Agents interact with each other and respond to events. PMRFSim allows an analyst to construct various what-if scenarios and generates numerous graphs that characterize the social landscape. This analysis is intended to aid public affairs officers understand the social landscape.

The availability of online documents coupled with emergent text mining methods has opened new research horizons. To achieve their potential, mining technologies need to be theoretically focused. We present data theory as a crucial component of text mining, and provide a substantive proto- theory from the synthesis of complex multigames, prototype concepts, and emotio-cognitive orientation fields. We discuss how the data theory presented informs the application of text mining to mining discourse(s) and how, in turn, this allows for modeling across contextual thresholds. Finally, the relationship between discourse mining, data theory, and thresholds is illustrated with an historical example, the events surrounding the 1992 civil war in Tajikistan.

A state is not alive, yet it performs many of the central enjoys few bonds of kinship: and residence depends upon functions of life like replication and adaptation to new conditions occupational specialization rather than blood relations. A to balance social protection and opportunity. As a modern state can declare war on behalf of the entire collectivity, lifelike system the rise of the modern state raises four sets reserving the right to declare mandatory participation of fundamental questions about its evolutionary design. A and to contract the area of private vengeance. They proclaim first set concerns how it became a sustainable, autonomously a monopoly of force and of law, while requiring citizens to replicating system, capable of evolution. All non-state agglomerations forgo violence; vengeance is not the responsibility of the offended such as empires or chiefdoms eventually stagnate party. Almost any crime against one member is a because they are closed systems that break down over crime against the state. Subgroups seeking vengeance are time (Weber). A state is an open system that must able to viewed as threatening to the order of the state.

Early studies of public budgeting emphasized uncertainty Two of us (BJ and FB) have published a set of papers, in the decision-making environment. Budgeting in the books focusing on annual budget changes (Jones and absence of information about the impacts of decisions led Baumgartner 2005b). Leptokurtic distribution of percentual to an adjustment process rooted in simple decision rules budget changes were observed in a broad range of settings: and bargaining among interests. This led to marginal or small increases and small decreases of budgets and budget incremental adjustments from the budgetary status quo, components are the most frequent, but time to time large with all major actors wary of big changes to the budgetary increases and cutoffs are observed as well.

Irregular Warfare (IW), with its emphasis on social and cognitive phenomena such as population sentiment, is a major new focus of the Department of Defense (DoD). One of the most important classes of IW action is Information Operations (IO), the use of information to influence sentiment. With the DoD’s new focus on IW comes the new need to analyze and forecast the effects of IO actions on population sentiment. Analysts at the DoD traditionally use Modeling and Simulation to analyze and forecast the effects of conventional warfare’s actions on the outcome of wars, but IW and IO in particular are far more complex than conventional physics-based simulations. DoD analysts are in the early stages of looking for scientifically rigorous methods in the Modeling and Simulation of IO’s complex effects. This paper presents the state of IO modeling and simulation in the DoD, using examples from several computer models now being used, in these early stages of IW analysis. It discusses how the ideas of Complex Adaptive Systems (CAS) and threshold events in particular may be incorporated into IO modeling in order to increase its scientific rigor, fidelity, and validity.

International law is a singular exception to the top-down systems of law within nations. It presents the puzzle of how the law can be created or changed in the absence of authoritative rule-making institutions. The present paper is part of a work in progress that locates the law-making apparatus of international law in a complex adaptive system. Herein the focus is on thresholds. The first and most detailed threshold describes the emergence of the complex adaptive system. The second threshold consists of the transformation of international law from the voluntary to the automatic. The third threshold is here but has not yet been crossed: actualizing human rights as enforceable claims by individuals against States.

The goal of this paper is to present four key assumptions regarding the measurement of cognitive and metacognitive regulatory processes used during learning with hypermedia. First, we assume it is possible to detect, trace, model, and foster SRL processes during learning with hypermedia. Second, understanding the complex nature of the regulatory processes during learning with hypermedia is critical in determining why certain processes are used throughout a learning task. Third, it is assumed that the use of SRL processes can dynamically change over time and that they are cyclical in nature (influenced by internal and external conditions and feedback mechanisms). Fourth, capturing, identifying, and classifying SRL processes used during learning with hypermedia is a rather challenging task.

Unfortunately, many students stop using these beneficial learning practices as soon Presented by Stephen Grossberg, Department of Cognitive as the metatutoring ceases. Apparently, the metatutors were and Neural Systems, Center for Adaptive Systems, and Center nagging rather than convincing. This talk will present a of Excellence for Learning in Education, Science, and study of Pyrenees, a metatutor that coaches students to focus Technology, Boston University, Boston, MA 02215 on learning domain principles rather than solutions to A deep and rational understanding of the factors that influence examples. It was convincing, in that students who were effective education and learning technologies depends taught probability with Pyrenees used principle-based problem on a corresponding understanding of how the brain in health solving on post-test more so than students taught by Andes, and disease controls learned behaviors. There has been a which did not focus students on principles. Moreover, revolution in discovering new computational paradigms, organizational when all students were transferred to Andes for learning principles, mechanisms, and models of how of physics, those who were metatutored used the principlefocused learning processes enable brains to give rise to minds.