Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

Overview on Agent-Based Social Modelling and the Use of Formal Languages

The use of agent-based modelling and simulation techniques in the social sciences has flourished in the recent decades. The main reason is that the object of study in these disciplines, human society present or past, is difficult to analyse through classical analytical techniques. Population dynamics and structures are inherently complex. Thus, other methodological techniques need to be found to more adequately study this field. In this context, agent-based modelling is encouraging the introduction of computer simulations to examine behavioural patterns in complex systems. Simulation provides a tool to artificially examine societies where a big number of actors with decision capacity coexist and interact. However, formal modelling in these areas has not traditionally been used compared to other fields of science, in particular in their use of formal languages during the modelling process. In this chapter, the authors aim to revise the most relevant aspects on modelling in social sciences and to discuss the use formal languages by social scientists

Land Use Change and Economic Opportunity in Amazonia: An Agent-based Model

Economic changes such as rising açaí prices and the availability of off-farm employment are transforming the landscape of the Amazonian várzea, subject to decision-making at the farming household level. Land use change results from complex human-environment interactions which can be addressed by an agent-based model. An agent-based model is a simulation model composed of autonomous interacting entities known as agents, built from the bottom-up. Coupled with cellular automata, which forms the agents’ environment, agent-based models are becoming an important tool of land use science, complementing traditional methods of induction and deduction. The decision-making methods employed by agent-based models in recent years have included optimization, imitation, heuristics, classifier systems and genetic algorithms, among others, but multiple methods have rarely been comparatively analyzed. A modular agent-based model is designed to allow the researcher to substitute alternative decision-making methods. For a smallholder farming community in Marajó Island near Ponta de Pedras, Pará, Brazil, 21 households are simulated over a 40-year period. In three major scenarios of increasing complexity, these households first face an environment where goods sell at a constant price throughout the simulated period and there are no outside employment opportunities. This is followed by a scenario of variable prices based on empirical data. The third scenario combines variable prices with limited employment opportunities, creating multi-sited households as members emigrate. In each scenario, populations of optimizing agents and heuristic agents are analyzed in parallel. While optimizing agents allocate land cells to maximize revenue using linear programming, fast and frugal heuristic agents use decision trees to quickly pare down feasible solutions and probabilistically select between alternatives weighted by expected revenue. Using distributed computing, the model is run through several parameter sweeps and results are recorded to a cenral database. Land use trajectories and sensitivity analyses highlight the relative biases of each decision-making method and illustrate cases where alternative methods lead to significantly divergent outcomes. A hybrid approach is recommended, employing alternative decision-making methods in parallel to illustrate inefficiencies exogenous and endogenous to the decision-maker, or allowing agents to select among multiple methods to mitigate bias and best represent their real-world analogues

Fabricate 2020

Fabricate 2020 is the fourth title in the FABRICATE series on the theme of digital fabrication and published in conjunction with a triennial conference (London, April 2020). The book features cutting-edge built projects and work-in-progress from both academia and practice. It brings together pioneers in design and making from across the fields of architecture, construction, engineering, manufacturing, materials technology and computation. Fabricate 2020 includes 32 illustrated articles punctuated by four conversations between world-leading experts from design to engineering, discussing themes such as drawing-to-production, behavioural composites, robotic assembly, and digital craft

Self sustainable cathodes for microbial fuel cells

The ultimate goal of this thesis was to investigate and produce an MFC with self-sustainable cathode so it could be implemented in real world applications. Using methods previously employed [polarisation curve experiments, power output measurements, chemical assays for determining COD in wastewater and other elements present in anolyte or catholyte, biomass assessments] and with a focus on the cathode, experiments were conducted to compare and contrast different designs, materials and nutrient input to microbial fuel cells with appropriate experimental control systems.Results from these experiments show that: Firstly, the choice of polymeric PEM membrane showed that the most effective materials in terms of power performance were cation exchange membranes. In terms of cost effectiveness the most promising was CM-I, which was the preferred separator for later experiments.Secondly, a completely biotic MFC with the algal cathode was shown to produce higher power output (7.00 mW/m2) than the abiotic control (1.52 mW/m2). At the scale of the experimental system, the reservoir of algal culture produced sufficient dissolved oxygen to serve the MFCs in light or dark conditions. To demonstrate usable power, 16 algal cathode-designed MFCs were used to power a dc pump as a practical application.It has been presented that the more power the MFC generates, the more algal biomass will be harvested in the connected photoreactor. The biomass grown was demonstrated to be a suitable carbon-energy resource for the same MFC units in a closed loop scenario, whereby the only energy into the system was light.In the open to air cathode configuration various modifications to the carbon electrode materials including Microporous Layer (MPL) and Activated Carbon (AC) showed catholyte synthesis directly on the surface of the electrode and elemental extraction such as Na, K, Mg, from wastewater in a power dependent manner. Cathode flooding has been identified as an important and beneficial factor for the first time in MFCs, and has been demonstrated as a carbon capture system through wet scrubbing of carbon dioxide from the atmosphere. The captures carbon dioxide was mineralised into carbonate and bicarbonate of soda (trona). The novel inverted, tubular MFC configuration integrates design and operational simplicity showing significantly improved performance rendering the MFC system feasible for electricity recovery from waste. The improved power (2.58 mW) from an individual MFC was increased by 5-fold compared to the control unit, and 2-fold to similar sized tubular systems reported in the literature; moreover it was able to continuously power a LED light, charge a mobile phone and run a windmill motor, which was not possible before

Design of Multi Agent Based Crowd Injury Model

A major concern of many government agencies is to predict and control the behavior of crowds in different situations. Many times such gatherings are legal, legitimate, and peaceful. But there are times when they can turn violent, run out of control, result in material damages and even casualties. It then becomes the duty of governments to bring them under control using a variety of techniques, including non-lethal and lethal weapons, if necessary. In order to aid decision makers on the course of action in crowd control, there are modeling and simulation tools that can provide guidelines by giving programmed rules to computer animated characters and to observe behaviors over time in appropriate scenarios. A crowd is a group of people attending a public gathering, with some joint purpose, such as protesting government or celebrating an event. In some countries these kinds of activities are the only way to express public\u27s displeasure with their governments. The governments\u27 reactions to such activities may or may not be tolerant. For these reasons, such situations must be eliminated by recognizing when and how they occur and then providing guidelines to mitigate them. Police or military forces use non-lethal weapons (NLWs), such as plastic bullets or clubs, to accomplish their job. In order to simulate the results of such actions in a computer, there is a need to determine the physical effects of NLWs over the individuals in the crowd. In this dissertation, a fuzzy logic based crowd injury model for determining the physical effects of NLWs is proposed. Fuzzy logic concepts can be applied to a problem by using linguistic rules, which are determined by problem domain experts. In this case, a group of police and military officers were consulted for a set of injury model rules and those rules were then included in the simulation platform. As a proof of concept, a prototype system was implemented using the Repast Simphony agent based simulation toolkit. Simulation results illustrated the effectiveness of the simulation framework

EvoCraft: A New Challenge for Open-Endedness

This paper introduces EvoCraft, a framework for Minecraft designed to study open-ended algorithms. We introduce an API that provides an open-source Python interface for communicating with Minecraft to place and track blocks. In contrast to previous work in Minecraft that focused on learning to play the game, the grand challenge we pose here is to automatically search for increasingly complex artifacts in an open-ended fashion. Compared to other environments used to study open-endedness, Minecraft allows the construction of almost any kind of structure, including actuated machines with circuits and mechanical components. We present initial baseline results in evolving simple Minecraft creations through both interactive and automated evolution. While evolution succeeds when tasked to grow a structure towards a specific target, it is unable to find a solution when rewarded for creating a simple machine that moves. Thus, EvoCraft offers a challenging new environment for automated search methods (such as evolution) to find complex artifacts that we hope will spur the development of more open-ended algorithms. A Python implementation of the EvoCraft framework is available at: https://github.com/real-itu/Evocraft-py

Optimisation of Microbial Fuel Cells (MFCs) through bacterial-robot interaction

For over 100 years, Microbial Fuel Cells (MFCs) have been developed as eco-friendly alternatives for generating electricity via the oxidation of organic matter by bacteria. In the early 2000s, collectives of MFCs were proven fea-sible energy providers for low-power robots such as Gastrobot and EcoBots. Even though individual MFC units are low in power, significant progress has been achieved in terms of MFC materials and configurations, enabling them to generate higher output levels. However, up to this date, MFCs are produced and matured using conventional laboratory methods that can take up to three months to bring the MFCs to their maximum power aptitudes. In this work, an approach to use a low-cost (£1.5k) RepRap liquid handling robot called EvoBot was employed with the aim to automate the maturing process of MFCs and allow them to reach their maximum power ability in a shorter time span. Initially, the work focused on establishing an interface and interconnection between the living cells (in the MFC) and the robotic platform, and investigating whether the MFC voltage can trigger a feedback loop feeding mechanism. It was shown that the robot successfully matured the MFCs in just 6 days and, they were also 1.4 times more powerful than conventionally matured MFCs (from 19.1 mW/m2 to 26.5 mW/m2). This work took a rounded approach in improving the overall MFC perfor-mance. 3D-printable materials that can emerge from EvoBot were investi-gated for fabricating MFCs. MFCs employing these materials improved their power output by almost 50% (from 66μW to 130 μW) compared to the ones based on conventional, fluorinated materials. Furthermore, EvoBot was able to improve the fuel supply frequency and composition using evolutionally algorithms. For the first time, this project has demonstrated that the fabrica-tion, maintenance and power generation of MFCs can be optimised via the interaction and support of a dedicated robotic system