Agent-based simulation with NetLogo to evaluate ambient intelligence scenarios

In This Paper An Agent-Based Simulation Is Developed In Order To Evaluate An Ambient Intelligence Scenario Based On Agents. Many Ami Applications Are Implemented Through Agents But They Are Not Compared With Any Other Existing Alternative In Order To Evaluate The Relative Benefits Of Using Them. The Proposed Simulation Environment Analyses Such Benefits Using Two Evaluation Criteria: First, Measuring Agent Satisfaction Of Different Types Of Desires Along The Execution. Second, Measuring Time Savings Obtained Through A Correct Use Of Context Information. In This Paper An Existing Agent Architecture, An Ontology And A 12-Steps Protocol To Provide Ami Services In Airports, Is Evaluated Using The Netlogo Simulation Environment. In Our Netlogo Model We Are Considering Scalability Issues Of This Application Domain But Using Fipa And Bdi Extensions To Be Coherent With Our Previous Works And Our Previous Jade Implementation Of Them. The Netlogo Model Simulates An Airport With Agent &#39 Passengers&#39 Passing Through Several Zones Located In A Specific Order In A Map: Passport Controls, Check-In Counters Of Airline Companies, Boarding Gates, Different Types Of Shopping. Although The Initial Data In Each Simulation Is Generated Randomly, And The Model Is Just An Approximation Of Real-World Airports, The Definition Of This Case Of Use Of Ami Through Netlogo Agents Opens An Interesting Way To Evaluate The Benefits Of Using Ami, Which Is A Significant Contribution To The Final Development Of Ami Systems.This work was partially funded by CNPq PVE Project 314017/2013-5, FAPERJ APQ1 Project 211.500/2015 and by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-0

How Resilient Are Our Societies? Analyses, Models, and Preliminary Results

Traditional social organizations such as those for the management of healthcare and civil defence are the result of designs and realizations that matched well with an operational context considerably different from the one we are experiencing today: A simpler world, characterized by a greater amount of resources to match less users producing lower peaks of requests. The new context reveals all the fragility of our societies: unmanageability is just around the corner unless we do not complement the "old recipes" with smarter forms of social organization. Here we analyze this problem and propose a refinement to our fractal social organizations as a model for resilient cyber-physical societies. Evidence to our claims is provided by simulating our model in terms of multi-agent systems.Comment: Paper submitted for publication in the Proc. of SERENE 2015 (http://serene.disim.univaq.it/2015/

Transmission Capacity as a Common-Pool Resource: The Case of Gas Interconnector Capacity

We investigated the very real problem of congestion at gas interconnectors. Instead of suggesting further incremental change to the European regulation in force to remedy congestion problems, we took a step back and consider gas interconnectors as a Common-Pool Resource (CPR). We suggest to wait and see what institutions the shippers let emerge to govern and manage interconnector capacity. To explore this idea, we developed a model to simulate the possible emergence of institutions that would coordinate the shippers and help overcome congestion. We simulate 40 shippers at the Dutch and Belgian interconnectors and allow them to autonomously book capacity. Agents can learn over time to improve their behaviour and coordinate with each other to collectively define a new institution in the system. The main simulator indicators are the observed booking behaviour, agent profits and emerging institutions. We present and discuss preliminary results from a set of simulation runs

Multi-agent simulations for emergency situations in an airport scenario

This paper presents a multi-agent framework using Net- Logo to simulate humanand collective behaviors during emergency evacuations. Emergency situationappears when an unexpected event occurs. In indoor emergency situation, evacuation plans defined by facility manager explain procedure and safety ways tofollow in an emergency situation. A critical and public scenario is an airportwhere there is an everyday transit of thousands of people. In this scenario theimportance is related with incidents statistics regarding overcrowding andcrushing in public buildings. Simulation has the objective of evaluating buildinglayouts considering several possible configurations. Agents could be based onreactive behavior like avoid danger or follow other agent, or in deliberative behaviorbased on BDI model. This tool provides decision support in a real emergencyscenario like an airport, analyzing alternative solutions to the evacuationprocess.Publicad

Perception Intelligence Integrated Vehicle-to-Vehicle Optical Camera Communication.

Ubiquitous usage of cameras and LEDs in modern road and aerial vehicles open up endless opportunities for novel applications in intelligent machine navigation, communication, and networking. To this end, in this thesis work, we hypothesize the benefit of dual-mode usage of vehicular built-in cameras through novel machine perception capabilities combined with optical camera communication (OCC). Current key conception of understanding a line-of-sight (LOS) scenery is from the aspect of object, event, and road situation detection. However, the idea of blending the non-line-of-sight (NLOS) information with the LOS information to achieve a see-through vision virtually is new. This improves the assistive driving performance by enabling a machine to see beyond occlusion. Another aspect of OCC in the vehicular setup is to understand the nature of mobility and its impact on the optical communication channel quality. The research questions gathered from both the car-car mobility modelling, and evaluating a working setup of OCC communication channel can also be inherited to aerial vehicular situations like drone-drone OCC. The aim of this thesis is to answer the research questions along these new application domains, particularly, (i) how to enable a virtual see-through perception in the car assisting system that alerts the human driver about the visible and invisible critical driving events to help drive more safely, (ii) how transmitter-receiver cars behaves while in the mobility and the overall channel performance of OCC in motion modality, (iii) how to help rescue lost Unmanned Aerial Vehicles (UAVs) through coordinated localization with fusion of OCC and WiFi, (iv) how to model and simulate an in-field drone swarm operation experience to design and validate UAV coordinated localization for group of positioning distressed drones. In this regard, in this thesis, we present the end-to-end system design, proposed novel algorithms to solve the challenges in applying such a system, and evaluation results through experimentation and/or simulation

Agoric computation: trust and cyber-physical systems

In the past two decades advances in miniaturisation and economies of scale have led to the emergence of billions of connected components that have provided both a spur and a blueprint for the development of smart products acting in specialised environments which are uniquely identifiable, localisable, and capable of autonomy. Adopting the computational perspective of multi-agent systems (MAS) as a technological abstraction married with the engineering perspective of cyber-physical systems (CPS) has provided fertile ground for designing, developing and deploying software applications in smart automated context such as manufacturing, power grids, avionics, healthcare and logistics, capable of being decentralised, intelligent, reconfigurable, modular, flexible, robust, adaptive and responsive. Current agent technologies are, however, ill suited for information-based environments, making it difficult to formalise and implement multiagent systems based on inherently dynamical functional concepts such as trust and reliability, which present special challenges when scaling from small to large systems of agents. To overcome such challenges, it is useful to adopt a unified approach which we term agoric computation, integrating logical, mathematical and programming concepts towards the development of agent-based solutions based on recursive, compositional principles, where smaller systems feed via directed information flows into larger hierarchical systems that define their global environment. Considering information as an integral part of the environment naturally defines a web of operations where components of a systems are wired in some way and each set of inputs and outputs are allowed to carry some value. These operations are stateless abstractions and procedures that act on some stateful cells that cumulate partial information, and it is possible to compose such abstractions into higher-level ones, using a publish-and-subscribe interaction model that keeps track of update messages between abstractions and values in the data. In this thesis we review the logical and mathematical basis of such abstractions and take steps towards the software implementation of agoric modelling as a framework for simulation and verification of the reliability of increasingly complex systems, and report on experimental results related to a few select applications, such as stigmergic interaction in mobile robotics, integrating raw data into agent perceptions, trust and trustworthiness in orchestrated open systems, computing the epistemic cost of trust when reasoning in networks of agents seeded with contradictory information, and trust models for distributed ledgers in the Internet of Things (IoT); and provide a roadmap for future developments of our research

Consensual negotiation-based decision making for connected appliances in smart home management systems

Recently, the concept of Internet of Agent has been introduced as a potential technology that pushes intelligence, data processing, analytics and communication capabilities down to the point where the data originates. In this paper, we introduce a novel approach for a Decentralized Home Energy Management System by applying the Internet of Agent concept. In particular, we first present an Internet of Agent framework in terms of sensing, communicating and collaborating among connected appliances. Then, the decentralized management based on consensual negotiation mechanism with several intelligent techniques are proposed for dynamic scheduling connected appliance. Specifically, by applying the Internet of Agent framework, connected appliances are regarded as smart agents that are able to make individual decisions by reaching agreement over the exchange of operations on competitive resources. Furthermore, in this study, the load balancing problem in which load shifting is able to reduce the electricity demand during peak hours is taken into account in order to emphasize the effectiveness of our approach. For the experiment, we develop a simulation of smart home environment to evaluate our approach using NetLogo, a tool which provides real-time analysis in the modeling and simulation domain of complex systems.This research was supported by the Chung-Ang University Research Grants in 2018. In addition, this work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2017R1A2B4010774)

An Energy-Aware Algorithm for Large Scale Foraging Systems

International audienceThe foraging task is one of the canonical testbeds for cooperative robotics, in which a collection of coordinated robots have to find and transport one or more objects to one or more specific storage points. Swarm robotics has been widely considered in such situations, due to its strengths such as robustness, simplicity and scalability. Typical multi-robot foraging systems currently consider tens to hundreds of agents. This paper presents a new algorithm called Energy-aware Cooperative Switching Algorithm for Foraging (EC-SAF) that manages thousands of robots. We investigate therefore the scalability of EC-SAF algorithm and the parameters that can affect energy efficiency overtime. Results indicate that EC-SAF is scalable and effective in reducing swarm energy consumption compared to an energy-aware version of the reference well-known c-marking algorithm (Ec-marking)

Assessing Health Vulnerability to Air Pollution in Seoul Using an Agent-Based Simulation

This study aims to investigate the exposure to air pollution in Seoul and the consequent health effects in Seoul South Korea, and suggest possible solutions using agent-based modelling (ABM). ABM is a useful technique that can simulate pollution generation and exposure, mobility patterns of unique individuals, and explore future scenarios. The first study compared Universal Kriging and Generalised Additive Models to spatially interpolate pollution station data over Seoul. A new method was discovered to enhance the accuracy of NO2 on roads. Next, ABM was used to evaluate potential health loss for a set of demographic groups after being cumulatively exposed to particulates (PM10), with a nominal heath impact threshold of 100µg/m3. Finally, a traffic simulation examined the coupled problem of non-exhaust emissions and behaviour and estimate exposure to PM10 for groups of drivers and pedestrians in central Seoul. Having tested the sensitivity to calibrated parameters, scenarios of traffic restriction and modification of pedestrian behaviour to avoid polluted areas was investigated. With less difference between interpolation methods, the result showed a remarkable contrast between roadside and background NO2 as well as a daily cycle, while PM10 had a small variance between hours but had greater seasonal oscillation. The first ABM study showed that disparities in health may arise as a result of differences in socioeconomic status, especially when the group was exposed over a long period, and road proximity caused additional health loss. In the traffic simulation study, extreme PM10 was found along roadways, but although drivers were exposed to extreme values, longer exposure for pedestrians led to higher health risks. Despite the absence of reliable data linking exposure to actual health effects, it is possible to make progress with ABM. In addition, pollution exposure can vary by commuting patterns and the urban development of one’s location. Scenarios can be advantageous for healthcare policy – to aid the most vulnerable groups and districts