Socioeconomic agents as active matter in nonequilibrium Sakoda-Schelling models

How robust are socioeconomic agent-based models with respect to the details of the agents' decision rule? We tackle this question by considering an occupation model in the spirit of the Sakoda-Schelling model, historically introduced to shed light on segregation dynamics among human groups. For a large class of utility functions and decision rules, we pinpoint the nonequilibrium nature of the agent dynamics, while recovering the equilibrium-like phase separation phenomenology. Within the mean field approximation we show how the model can be mapped, to some extent, onto an active matter field description (Active Model B). Finally, we consider non-reciprocal interactions between two populations, and show how they can lead to non-steady macroscopic behavior. We believe our approach provides a unifying framework to further study geography-dependent agent-based models, notably paving the way for joint consideration of population and price dynamics within a field theoretic approach.Comment: 12 pages, 7 figure

Fractal self-organization of bacteria-inspired agents

We develop an agent-based model as a preliminary theoretical basis to guide the synthesis of a new class of materials with dynamic properties similar to bacterial colonies. Each agent in the model is representative of an individual bacterium capable of: the uptake of chemicals (nutrients), which are metabolized; active movement (part viscous, part diffusive), consuming metabolic energy; and cellular division, when agents have doubled in size. The agents grow in number and self-organize into fractal structures, depending on the rules that define the actions of the agents and the parameter values. The environment of the agents includes chemicals responsible for their growth and is described by a diffusion-reaction equation with Michaelis-Menten kinetics. These rules are modeled mathematically by a set of equations with five dimensionless groups that are functions of physical parameters. Simulations are performed for different parameter values. The resulting structures are characterized by their fractal scaling regime, box-counting and mass-radius dimensions, and lacunarity. Each parameter influences the overall structure in a unique way, generating a wide spectrum of structures. For certain combinations of parameter values, the model converges to a steady state, with a finite population of agents that no longer divide. © 2012 World Scientific Publishing Company

Self–organised multi agent system for search and rescue operations

Autonomous multi-agent systems perform inadequately in time critical missions, while they tend to explore exhaustively each location of the field in one phase with out selecting the pertinent strategy. This research aims to solve this problem by introducing a hierarchy of exploration strategies. Agents explore an unknown search terrain with complex topology in multiple predefined stages by performing pertinent strategies depending on their previous observations. Exploration inside unknown, cluttered, and confined environments is one of the main challenges for search and rescue robots inside collapsed buildings. In this regard we introduce our novel exploration algorithm for multi–agent system, that is able to perform a fast, fair, and thorough search as well as solving the multi–agent traffic congestion. Our simulations have been performed on different test environments in which the complexity of the search field has been defined by fractal dimension of Brownian movements. The exploration stages are depicted as defined arenas of National Institute of Standard and Technology (NIST). NIST introduced three scenarios of progressive difficulty: yellow, orange, and red. The main concentration of this research is on the red arena with the least structure and most challenging parts to robot nimbleness

Exploring evidence based management in the National Health Service

Purpose and aims of the study: To contribute to the on-going debate over whether the use of evidence could and should improve organisational effectiveness. This is especially important in the context of the health service that has, since (May 1997) enthusiastically adopted evidence based medicine as its method of health delivery. To develop a practical explanation for policy makers and managers on how and where evidence based management is used appropriately. Justification: Kovner and Rundall (2006 p3) said “the sense of urgency associated with improving the quality of medical care does not exist with respect to improving the quality of management decision making. A more evidence based approach would improve the competence of the decision makers and their motivation to use more scientific methods when making a decision”. The paper reviews the conclusion of Kovner and Rundall (2006) (an American study) within the context of the UK National Health Service. There is a need to develop a theoretical framework of how and why evidence is (or is not) used by managers in the NHS. Motivation: The author holds a senior management position in the National Health Service. The author has performed the role of Director and Chief Executive in NHS organisations since 2000. These organisations have been surplus making, target hitting, award winning, credited by the auditors and successful in the eyes of the regulators. Unfortunately over the last few years the author has been in a quandary about something. Are NHS managers as a group of professionals, using policies that solved the wrong problem or solving the right problem, but still in the wrong way? Following this line of thought, the author wanted to ask "why don’t executives in the NHS make evidence based decisions?