A multi-agent approach for enhancing transient stability of smart grids

Transient stability, an important issue to avoid the loss of synchronous operation in power systems, can be achieved through proper coordination and operation of protective devices within the critical clearing time (CCT). In view of this, the development of an intelligent decision support system is useful for providing better protection relay coordination. This paper presents an intelligent distributed agent-based scheme to enhance the transient stability of smart grids in light of CCT where a multi-agent framework (MAF) is developed and the agents are represented in such a way that they are equipped with protection relays (PRs). In addition to this, an algorithm is developed which assists the agents to make autonomous decision for controlling circuit breakers (CBs) independently. The proposed agents are responsible for the coordination of protection devices which is done through the precise detection and isolation of faults within the CCT. The agents also perform the duty of reclosing CBs after the clearance of faults. The performance of the proposed approach is demonstrated on a standard IEEE 39-bus test system by considering short-circuit faults at different locations under various load conditions. To further validate the suitability of the proposed scheme a benchmark 16-machine 68-bus power system is also considered. Simulation results show that MAF exhibits full flexibility to adapt the changes in system configurations and increase the stability margin for both test systems.

Recognition: combining human interaction and a digital performing agent

Virtual and augmented environments are often dependent on human intervention for change to occur. However there are times when it would be advantageous for appropriate human-like activity to still occur when there are no humans present. In this paper, we describe the installation art piece Recognition, which uses the movement of human participants to effect change, and the movement of a performing agent when there are no humans present. The agent's Artificial Neural Network has learnt appropriate movements from a dancer and is able to generate suitable movement for the main avatar in the absence of human participants.

Zinc doped ferrite magnetic resonance imaging contrast agent for atherosclerosis

 This project focuses on the development of zinc doped ferrite nanoparticle based MRI contrast agents with enhanced contrast and site-specific targeting for atherosclerosis diagnosis. The engineered nanocomplexes developed were validated through MRI scans using rat models with potential for multimodal imaging and effective therapy.

Youth Depression Alleviation-Augmentation with an anti-inflammatory agent (YoDA-A): protocol and rationale for a placebo-controlled randomized trial of rosuvastatin and aspirin

AIM: There is growing support for the role of inflammation and oxidative stress in the pathophysiology of major depressive disorder (MDD). This has led to the development of novel strategies targeting inflammation in the treatment of depression. Rosuvastatin and aspirin have well-documented, anti-inflammatory and antioxidant properties. The aim of the Youth Depression Alleviation: Augmentation with an anti-inflammatory agent (YoDA-A) study is to determine whether individuals receiving adjunctive anti-inflammatory agents, aspirin and rosuvastatin experience a reduction in the severity of MDD compared with individuals receiving placebo. METHODS: YoDA-A is a 12-week triple-blind, randomized controlled trial funded by the National Health and Medical Research Council, Australia. Participants aged 15-25, with moderate-to-severe MDD, are allocated to receive either 10 mg/day rosuvastatin, 100 mg/day aspirin, or placebo, in addition to treatment as usual. Participants are assessed at baseline and at weeks 4, 8, 12 and 26. The primary outcome is change in the Montgomery-Åsberg Depression Rating Scale (MADRS) from baseline to week 12. RESULTS: The study is planned to be completed in 2017. At date of publication, 85 participants have been recruited. CONCLUSION: Timely and targeted intervention for youth MDD is crucial. Given the paucity of new agents to treat youth MDD, adjunctive trials are not only pragmatic and 'real-world', but additionally aim to target shortfalls in conventional medications. This study has the potential to first provide two new adjunctive treatment options for youth MDD; aspirin and rosuvastatin. Second, this study will serve as proof of principle of the role of inflammation in MDD.

A decentralised multi-agent approach to enhance the stability of smart microgrids with renewable energy

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

Distributed agent-based control scheme for single-phase parallel inverters in microgrids with photovoltaic systems

In this paper, an agent-based distributed control scheme is presented to control single-phase parallel inverters in solar photovoltaic (PV) systems connected to microgrids. A communication assisted multi-agent framework is developed within microgrids where agents perform their tasks in a distributed manner with an aim of stabilizing load voltage and current under normal and faulted conditions through the asymptotic tracking of the reference current signal. The distributed agent-based control scheme requires information from the neighboring agents through communication network to decide control actions. The proposed control scheme utilizes Ziegler-Nichols (Z-N) tuning approach to design proportional integral (PI) controllers for controlling inverters within the multi-agent system (MAS). A microgrid with parallel inverter-connected solar PV systems is considered for simulations under normal and faulted conditions where results show the excellency of the proposed agent-based scheme in comparison to the conventional scheme without MAS.

Adding a new anticoagulant or antiplatelet agent for patient receiving aspirin after an acute coronary syndrome? - Results from a pairwise and network meta-analysis of randomized-controlled trials

 Objectives: To synthesize the efficacy and safety outcomes from randomized-controlled trials (RCTs) regarding new oral anticoagulant, protease-activated receptor-1 (PAR-1) antagonist, and warfarin adjunctive to aspirin for patients after acute coronary syndrome (ACS) via pair-wise and network meta-analyses.
Methods: A comprehensive literature search was performed in Embase, Medline, Cochrane Library Web of Knowledge, and Scopus. The pair-wise meta-analysis was undertaken respectively to each agent/treatment category via Revmen 5.1. In order to estimate the relative efficacy of each agent/treatment category whilst preserving the randomized comparisons within each trial, a Bayesian network meta-analysis was conducted in WinBUGS using both fixed- and random-effects model. Covariate analysis was performed to explore the effects of length of follow-up and age of subject on the final results.
Results: In total, 23 RCTs were included in the meta-analysis. As shown by the results (OR,95%CI) for the pair-wise meta-analysis, new oral anticoagulants (0.85, [0.78, 0.93] and 3.04, [2.21, 4.19]), PAR-1 antagonists (0.80, [0.52, 1.22] and 1.55, [1.25, 1.93]) and warfarin (0.87, [0.74, 1.02] and 1.77, [1.46, 2.14]) might be able to provide better outcome in the incidences of major adverse events (MAE) but with higher bleeding risk comparing to aspirin treatment alone. Based on the model fit assessment, the random-effects model was adopted. The network meta-analysis (treatment effect comparing to aspirin lone) identified ximelagatran (-0.3044, [-0.8601, 0.2502]), dabigatran (-0.2144, [-0.8666, 0.4525]), rivoroxaban (-0.2179, [-0.5986, 0.1628]) and vorapaxar (-0.2272, [-0.81, 0.1664]) produced better improvements in MAE incidences whereas vorapaxar (0.3764, [-0.4444, 1.124]), warfarin (0.663, [0.3375, 1.037]), ximelagatran (0.7509, [-0.4164, 2.002]) and apixaban (0.8594, [-0.0049, 1.7]) produced less major bleeding events. The indirect comparisons among drug category (difference in incidence comparing to aspirin lone) showed new oral anticoagulants (-0.1974, [-0.284, -0.111]) and PAR-1 antagonists (-0.1239, [-0.215, -0.033]) to besuperior to warfarin (-0.1004, [-0.166, -0.035]) in the occurrences of MAE whereas PAR-1 antagonists (0.4292, [0.2123, 0.6476]) afforded better outcomes in major bleeding events against warfarin (0.5742, [0.3889, 0.7619]) and new oral anticoagulants (1.169, [0.8667, 1.485]).
Conclusion: Based on the study results, we cannot recommend the routine administration of new oral anticoagulant as add-on treatment for patients after ACS. However, for ACS patients comorbid with atrial fibrillation, new oral anticoagulant might be superior to warfarin in both efficacy and safety outcomes.

ANGEL: agent-based scheduling for real-time tasks in virtualized clouds

The success of cloud computing makes an increasing number of real-time applications such as signal processing and weather forecasting run in the cloud. Meanwhile, scheduling for real-time tasks is playing an essential role for a cloud provider to maintain its quality of service and enhance the system's performance. In this paper, we devise a novel agent-based scheduling mechanism in cloud computing environment to allocate real-time tasks and dynamically provision resources. In contrast to traditional contract net protocols, we employ a bidirectional announcement-bidding mechanism and the collaborative process consists of three phases, i.e., basic matching phase, forward announcement-bidding phase and backward announcement-bidding phase. Moreover, the elasticity is sufficiently considered while scheduling by dynamically adding virtual machines to improve schedulability. Furthermore, we design calculation rules of the bidding values in both forward and backward announcement-bidding phases and two heuristics for selecting contractors. On the basis of the bidirectional announcement-bidding mechanism, we propose an agent-based dynamic scheduling algorithm named ANGEL for real-time, independent and aperiodic tasks in clouds. Extensive experiments are conducted on CloudSim platform by injecting random synthetic workloads and the workloads from the last version of the Google cloud tracelogs to evaluate the performance of our ANGEL. The experimental results indicate that ANGEL can efficiently solve the real-time task scheduling problem in virtualized clouds.

Duet: Improvising spatial dialogues with an artificially intelligent agent

This paper presents an experimental framework for a virtual reality artwork, Duet, that employs a combination of live, full body motion capture and Oculus Rift HMD to construct an experience through which a human User can spatially interact with an artificially intelligent Agent. The project explores conceptual notions of embodied knowledge transfer, shared poetics of movement and distortions of the body schema. Within this context, both the User and the Agent become performers, constructing an intimate and spontaneously generated proximal space. The project generates a visualization of the relationship between the User and the Agent without the context of a fixed VR landscape or architecture. The Agent's ability to retain and accumulate movement knowledge in a way that mimics human learning transforms an interactive experience into a collaborative one. The virtual representation of both performers is distorted and amplified in a dynamic manner, enhancing the potential for creative dialogue between the Agent and the User.

Distributed multi-agent scheme to improve dynamic voltage stability of distribution networks

In this paper, a distributed multi-agent scheme is presented for reactive power management with renewable energy sources (RESs). The multi-agent system (MAS) framework is developed for distribution systems to improve the stability which is mostly dominated by voltage and the agents in this framework coordinate among themselves using online information and energy flow. In this paper, the agents basically perform two tasks- reactive power estimation and necessary control actions. The topology of distribution network is used to estimate the required reactive power for maintaining voltage stability where distributed static synchronous compensators (DSTATCOMs) are used to supply this reactive power. The DSTATCOM is controlled by using a linear quadratic regulator (LQR) controller within the agent framework. The proposed scheme is further compared with the conventional approach to validate the simulation results.

Using an animated pedagogical agent to interact affectively with the student

This work proposes an animated pedagogical agent that has the role of providing emotional support to the student: motivating and encouraging him, making him believe in his self-ability, and promoting a positive mood in him, which fosters learning. This careful support of the agent, its affective tactics, is expressed through emotional behaviour and encouragement messages of the lifelike character. Due to human social tendency of anthropomorphising software, we believe that a software agent can accomplish this affective role. In order to choose the adequate affective tactics, the agent should also know the student’s emotions. The proposed agent recognises the student’s emotions: joy/distress, satisfaction/disappointment, anger/gratitude, and shame, from the student’s observable behaviour, i. e. his actions in the interface of the educational system. The inference of emotions is psychologically grounded on the cognitive theory of emotions. More specifically, we use the OCC model which is based on the cognitive approach of emotion and can be computationally implemented. Due to the dynamic nature of the student’s affective information, we adopted a BDI approach to implement the affective user model and the affective diagnosis. Besides, in our work we profit from the reasoning capacity of the BDI approach in order for the agent to deduce the student’s appraisal, which allows it to infer the student’s emotions. As a case study, the proposed agent is implemented as the Mediating Agent of MACES: an educational collaborative environment modelled as a multi-agent system and pedagogically based on the sociocultural theory of Vygotsky.

Business competition dynamics: agent-based modeling simulations of firms in search of economic performance

A intenção deste trabalho é explorar dinâmicas de competição por meio de “simulação baseada em agentes”. Apoiando-se em um crescente número de estudos no campo da estratégia e teoria das organizações que utilizam métodos de simulação, desenvolveu-se um modelo computacional para simular situações de competição entre empresas e observar a eficiência relativa dos métodos de busca de melhoria de desempenho teorizados. O estudo também explora possíveis explicações para a persistência de desempenho superior ou inferior das empresas, associados às condições de vantagem ou desvantagem competitiva

Essays in heterogeneous agent macroeconomics

This thesis is comprised of three chapters. The first article studies the determinants of the labor force participation of elderly American males and investigates the factors that may account for the changes in retirement between 1950 and 2000. We develop a life-cycle general equilibrium model with endogenous retirement that embeds Social Security legislation and Medicare. Individuals are ex ante heterogeneous with respect to their preferences for leisure and face uncertainty about labor productivity, health status and out-of-pocket medical expenses. The model is calibrated to the U.S. economy in 2000 and is able to reproduce very closely the retirement behavior of the American population. It reproduces the peaks in the distribution of Social Security applications at ages 62 and 65 and the observed facts that low earners and unhealthy individuals retire earlier. It also matches very closely the increase in retirement from 1950 to 2000. Changes in Social Security policy - which became much more generous - and the introduction of Medicare account for most of the expansion of retirement. In contrast, the isolated impact of the increase in longevity was a delaying of retirement. In the second article, I develop an overlapping generations model of criminal behavior, which extends prior research on crime by taking into account individuals' labor supply decisions and the stigma effect that affects convicted offenders, lowering their likelihood of employment. I use the model to guide a quantitative assessment of the determinants of crime and of a counterfactual experiment in which an income redistribution policy is thought as an alternative to greater law enforcement. The model economy considered in this paper is populated by heterogeneous agents who live for a realistic number of periods, have preferences over consumption and leisure, and differ in terms of their age, their skills as well as their employment shocks. In addition, savings may be precautionary and allow partial insurance against the labor income shocks. Because of the lack of full insurance, this model generates an endogenous distribution of wealth across consumers, enabling us to assess the welfare implications of the redistribution policy experiment. I calibrated the model using the US data for 1980 and then use the model to investigate the changes in criminality between 1980 and 1996. The main results that come out of this study are: 1) Law enforcement policy was the most important factor behind the fall in criminality in the period, while the increase in inequality was the most important single factor promoting crime; 2) Stigmatization is not a free-cost crime control policy; 3) Income redistribution can be a powerful alternative policy to fight crime. Finally, the third article studies the impact of HIV/AIDS on per capita income and education. It explores two channels from HIV/AIDS to income that have not been sufficiently stressed by the literature: the reduction of the incentives to study due to shorter expected longevity and the reduction of productivity of experienced workers. In the model individuals live for three periods, may get infected in the second period and with some probability die of Aids before reaching the third period of their life. Parents care for the welfare of the future generations so that they will maximize lifetime utility of their dynasty. The simulations predict that the most affected countries in Sub-Saharan Africa will be in the future, on average, thirty percent poorer than they would be without AIDS. Schooling will decline in some cases by forty percent. These figures are dramatically reduced with widespread medical treatment, as it increases the survival probability and productivity of infected individuals.

Bank networks and firm credit: an agent based model approach

Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking where, according to the literature, the interaction over time between Banks and Firms are able to produce mutual benefits, mainly due to reduction of the information asymmetry between them. The following experiment is related to information heterogeneity in the credit market, where the larger the bank, the higher their visibility in the credit market, increasing the number of consult for new loans. Finally, the third experiment is about the effects on the credit market of the heterogeneity of prices that Firms faces in the goods market.