System Issues in Multi-agent Simulation of Large Crowds

Crowd simulation is a complex and challenging domain. Crowds demonstrate many complex behaviours and are consequently difficult to model for realistic simulation systems. Analyzing crowd dynamics has been an active area of research and efforts have been made to develop models to explain crowd behaviour. In this paper we describe an agent based simulation of crowds, based on a continuous field force model. Our simulation can handle movement of crowds over complex terrains and we have been able to simulate scenarios like clogging of exits during emergency evacuation situations. The focus of this paper, however, is on the scalability issues for such a multi-agent based crowd simulation system. We believe that scalability is an important criterion for rescue simulation systems. To realistically model a disaster scenario for a large city, the system should ideally scale up to accommodate hundreds of thousands of agents. We discuss the attempts made so far to meet this challenge, and try to identify the architectural and system constraints that limit scalability. Thereafter we propose a novel technique which could be used to richly simulate huge crowds

Decentralised Dynamic Task Allocation Using Overlapping Potential Games

This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a stochastic game formulation of these problems in which tasks have varying hard deadlines and processing requirements. We then introduce a new technique for approximating this game using a series of static potential games, before detailing a decentralised method for solving the approximating games that uses the distributed stochastic algorithm. Finally, we discuss an implementation of our approach to a task allocation problem in the RoboCup Rescue disaster management simulator. The results show that our technique performs comparably to a centralised task scheduler (within 6% on average), and also, unlike its centralised counterpart, it is robust to restrictions on the agents’ communication and observation ranges

Cooperatives for demand side management

We propose a new scheme for efficient demand side management for the Smart Grid. Specifically, we envisage and promote the formation of cooperatives of medium-large consumers and equip them (via our proposed mechanisms) with the capability of regularly participating in the existing electricity markets by providing electricity demand reduction services to the Grid. Based on mechanism design principles, we develop a model for such cooperatives by designing methods for estimating suitable reduction amounts, placing bids in the market and redistributing the obtained revenue amongst the member agents. Our mechanism is such that the member agents have no incentive to show artificial reductions with the aim of increasing their revenue

Microstructural Alterations and Oligodendrocyte Dysmaturation in White Matter After Cardiopulmonary Bypass in a Juvenile Porcine Model.

BACKGROUND: Newly developed white matter (WM) injury is common after cardiopulmonary bypass (CPB) in severe/complex congenital heart disease. Fractional anisotropy (FA) allows measurement of macroscopic organization of WM pathology but has rarely been applied after CPB. The aims of our animal study were to define CPB-induced FA alterations and to determine correlations between these changes and cellular events after congenital heart disease surgery. METHODS AND RESULTS: Normal porcine WM development was first assessed between 3 and 7 weeks of age: 3-week-old piglets were randomly assigned to 1 of 3 CPB-induced insults. FA was analyzed in 31 WM structures. WM oligodendrocytes, astrocytes, and microglia were assessed immunohistologically. Normal porcine WM development resembles human WM development in early infancy. We found region-specific WM vulnerability to insults associated with CPB. FA changes after CPB were also insult dependent. Within various WM areas, WM within the frontal cortex was susceptible, suggesting that FA in the frontal cortex should be a biomarker for WM injury after CPB. FA increases occur parallel to cellular processes of WM maturation during normal development; however, they are altered following surgery. CPB-induced oligodendrocyte dysmaturation, astrogliosis, and microglial expansion affect these changes. FA enabled capturing CPB-induced cellular events 4 weeks postoperatively. Regions most resilient to CPB-induced FA reduction were those that maintained mature oligodendrocytes. CONCLUSIONS: Reducing alterations of oligodendrocyte development in the frontal cortex can be both a metric and a goal to improve neurodevelopmental impairment in the congenital heart disease population. Studies using this model can provide important data needed to better interpret human imaging studies

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Decentralised Approaches for Self-Adaptation in Agent Organisations

Self-organising multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, decentralised approach for structural adaptation in explicitly modelled problem solving agent organisations. Based on self-organisation principles, our method enables the autonomous agents to modify their structural relations to achieve a better allocation of tasks in a simulated task-solving environment. Specifically, the agents reason about when and how to adapt using only their history of interactions as guidance. We empirically show that, in a wide range of closed, open, static and dynamic scenarios, the performance of organisations using our method is close (70-90%) to that of an idealised centralised allocation method and is considerably better (10-60%) than the current state of the art decentralised approaches

Self-Organising Agent Organisations

Self-organising multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, decentralised approach for structural adaptation in explicitly modelled problem solving agent organisations. Based on self-organisation principles, our method enables the agents to modify their structural relations to achieve a better allocation of tasks in a simulated task-solving environment. The agents reason on when and how to adapt using only their history of interactions as guidance. We empirically show that, in both closed and dynamic organisations, the performance of organisations using our method is close to that of an upper bound centralised allocation method and considerably better than a random adaptation method

Decentralised Dynamic Task Allocation: A Practical Game–Theoretic Approach

This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a Markov game formulation of these problems for tasks with varying hard deadlines and processing requirements. We then introduce a new technique for approximating this game using a series of static potential games, before detailing a decentralised solution method for the approximating games that uses the Distributed Stochastic Algorithm. Finally, we discuss an implementation of our approach to a task allocation problem in the RoboCup Rescue disaster management simulator. Our results show that our technique performs comparably to a centralised task scheduler (within 6% on average), and also, unlike its centralised counterpart, it is robust to restrictions on the agents' communication and observation range