Agent Based Modeling and Simulation: An Informatics Perspective

The term computer simulation is related to the usage of a computational model in order to improve the understanding of a system's behavior and/or to evaluate strategies for its operation, in explanatory or predictive schemes. There are cases in which practical or ethical reasons make it impossible to realize direct observations: in these cases, the possibility of realizing 'in-machina' experiments may represent the only way to study, analyze and evaluate models of those realities. Different situations and systems are characterized by the presence of autonomous entities whose local behaviors (actions and interactions) determine the evolution of the overall system; agent-based models are particularly suited to support the definition of models of such systems, but also to support the design and implementation of simulators. Agent-Based models and Multi-Agent Systems (MAS) have been adopted to simulate very different kinds of complex systems, from the simulation of socio-economic systems to the elaboration of scenarios for logistics optimization, from biological systems to urban planning. This paper discusses the specific aspects of this approach to modeling and simulation from the perspective of Informatics, describing the typical elements of an agent-based simulation model and the relevant research.Multi-Agent Systems, Agent-Based Modeling and Simulation

TOWARD A PLATFORM FOR MULTI-LAYERED MULTI-AGENT SITUATED SYSTEM (MMASS)-BASED SIMULATIONS: FOCUSING ON FIELD DIFFUSION

The paper introduces some issues and related solutions adopted in order to realize the MMASS platform. This is a framework to specify and execute simulation applications based on the multilayered multi-agent situated system model (MMASS). MMASS is a model for multi-agent systems (MAS) situated in an environment whose structure is explicitly defined. The behavior and interaction models of MMASS agents are strongly related to the spatial structure of their environment. The MMASS model is the result of a long-term research that has its roots and motivations on application domains and problems that require spatial features to be considered. Our experiences with these problems have concerned the design of domain models and their implementations, according to the MAS approach for simulation purposes. This activity has revealed that currently available tools do not support the management of spatial features of agent environment and interaction mechanisms defined by the MMASS model and thus they are not suitable for our purposes. The paper focuses on the MMASS platform that aims to support the specification and development of applications (mainly, simulations) based on MMASS. Design issues and related solutions that have been adopted in order to manage those aspects that characterize the MMASS model will be shown. After a description of the conceptual model that underlies the MMASS platform and its general architecture, we will overview how the platform supports the specification of agent structured environment, behavior and interaction, and how it supports the execution of agent actions and interactions. Then we will describe issues and adopted solutions (both algorithmic and implementative ones) to manage at-a-distance interaction among MMASS agents

Stopping Police in Their Tracks: Protecting Cellular Location Information Privacy in the Twenty-First Century

Only a small fraction of law enforcement agencies in the United States obtain a warrant before tracking the cell phones of suspects and persons of interest. This is due, in part, to the fact that courts have struggled to keep pace with a changing technological landscape. Indeed, courts around the country have issued a disparate array of holdings on the issue of warrantless cell phone tracking. This lack of judicial uniformity has led to confusion for both law enforcement agencies and the public alike. In order to protect reasonable expectations of privacy in the twenty-first century, Congress should pass legislation requiring law-enforcement agencies to obtain a warrant based upon probable cause before they can track a cell phone except in a limited set of time-sensitive situations and emergencies. This Issue Brief describes the technology police use to track cell phones, discusses the need for federal legislation, concludes that current Fourth Amendment jurisprudence is inadequate to address cell phone tracking, analyzes two bills dealing with “geolocation information” privacy that legislators have introduced in Congress, and ultimately concludes that one of those bills is superior to the other

Multiagent System Applied to the Modeling and Simulation of Pedestrian Traffic in Counterflow

An agent-based model to simulate a pedestrian crowd in a corridor is presented. Pedestrian crowd models are valuable tools to gain insight into the behavior of human crowds in both, everyday and crisis situations. The main contribution of this work is the definition of a pedestrian crowd model by applying ideas from the field of the kinetic theory of living systems on the one hand, and ideas from the field of computational agents on the other hand. Such combination supported a quantitative characterization of the performance of our agents, a neglected issue in agent-based models, through well-known kinetic parameters. Fundamental diagrams of flow and activity are presented for both, groups of homogeneous pedestrians, and groups of heterogeneous pedestrians in terms of their willingness to reach their goals.Agent-Based Modeling, Pedestrian Crowd, Activity Measurement

Can geocomputation save urban simulation? Throw some agents into the mixture, simmer and wait ...

There are indications that the current generation of simulation models in practical, operational uses has reached the limits of its usefulness under existing specifications. The relative stasis in operational urban modeling contrasts with simulation efforts in other disciplines, where techniques, theories, and ideas drawn from computation and complexity studies are revitalizing the ways in which we conceptualize, understand, and model real-world phenomena. Many of these concepts and methodologies are applicable to operational urban systems simulation. Indeed, in many cases, ideas from computation and complexity studies—often clustered under the collective term of geocomputation, as they apply to geography—are ideally suited to the simulation of urban dynamics. However, there exist several obstructions to their successful use in operational urban geographic simulation, particularly as regards the capacity of these methodologies to handle top-down dynamics in urban systems. This paper presents a framework for developing a hybrid model for urban geographic simulation and discusses some of the imposing barriers against innovation in this field. The framework infuses approaches derived from geocomputation and complexity with standard techniques that have been tried and tested in operational land-use and transport simulation. Macro-scale dynamics that operate from the topdown are handled by traditional land-use and transport models, while micro-scale dynamics that work from the bottom-up are delegated to agent-based models and cellular automata. The two methodologies are fused in a modular fashion using a system of feedback mechanisms. As a proof-of-concept exercise, a micro-model of residential location has been developed with a view to hybridization. The model mixes cellular automata and multi-agent approaches and is formulated so as to interface with meso-models at a higher scale

Interaction dynamics and autonomy in cognitive systems

The concept of autonomy is of crucial importance for understanding life and cognition. Whereas cellular and organismic autonomy is based in the self-production of the material infrastructure sustaining the existence of living beings as such, we are interested in how biological autonomy can be expanded into forms of autonomous agency, where autonomy as a form of organization is extended into the behaviour of an agent in interaction with its environment (and not its material self-production). In this thesis, we focus on the development of operational models of sensorimotor agency, exploring the construction of a domain of interactions creating a dynamical interface between agent and environment. We present two main contributions to the study of autonomous agency: First, we contribute to the development of a modelling route for testing, comparing and validating hypotheses about neurocognitive autonomy. Through the design and analysis of specific neurodynamical models embedded in robotic agents, we explore how an agent is constituted in a sensorimotor space as an autonomous entity able to adaptively sustain its own organization. Using two simulation models and different dynamical analysis and measurement of complex patterns in their behaviour, we are able to tackle some theoretical obstacles preventing the understanding of sensorimotor autonomy, and to generate new predictions about the nature of autonomous agency in the neurocognitive domain. Second, we explore the extension of sensorimotor forms of autonomy into the social realm. We analyse two cases from an experimental perspective: the constitution of a collective subject in a sensorimotor social interactive task, and the emergence of an autonomous social identity in a large-scale technologically-mediated social system. Through the analysis of coordination mechanisms and emergent complex patterns, we are able to gather experimental evidence indicating that in some cases social autonomy might emerge based on mechanisms of coordinated sensorimotor activity and interaction, constituting forms of collective autonomous agency

Enaction-Based Artificial Intelligence: Toward Coevolution with Humans in the Loop

This article deals with the links between the enaction paradigm and artificial intelligence. Enaction is considered a metaphor for artificial intelligence, as a number of the notions which it deals with are deemed incompatible with the phenomenal field of the virtual. After explaining this stance, we shall review previous works regarding this issue in terms of artifical life and robotics. We shall focus on the lack of recognition of co-evolution at the heart of these approaches. We propose to explicitly integrate the evolution of the environment into our approach in order to refine the ontogenesis of the artificial system, and to compare it with the enaction paradigm. The growing complexity of the ontogenetic mechanisms to be activated can therefore be compensated by an interactive guidance system emanating from the environment. This proposition does not however resolve that of the relevance of the meaning created by the machine (sense-making). Such reflections lead us to integrate human interaction into this environment in order to construct relevant meaning in terms of participative artificial intelligence. This raises a number of questions with regards to setting up an enactive interaction. The article concludes by exploring a number of issues, thereby enabling us to associate current approaches with the principles of morphogenesis, guidance, the phenomenology of interactions and the use of minimal enactive interfaces in setting up experiments which will deal with the problem of artificial intelligence in a variety of enaction-based ways

Development of antiseptic adaptation and cross-adapatation in selected oral pathogens in vitro

There is evidence that pathogenic bacteria can adapt to antiseptics upon repeated exposure. More alarming is the concomitant increase in antibiotic resistance that has been described for some pathogens. Unfortunately, effects of adaptation and cross-adaptation are hardly known for oral pathogens, which are very frequently exposed to antiseptics. Therefore, this study aimed to determine the in vitro increase in minimum inhibitory concentrations (MICs) in oral pathogens after repeated exposure to chlorhexidine or cetylpyridinium chloride, to examine if (cross-)adaptation to antiseptics/antibiotics occurs, if (cross-)adaptation is reversible and what the potential underlying mechanisms are. When the pathogens were exposed to antiseptics, their MICs significantly increased. This increase was in general at least partially conserved after regrowth without antiseptics. Some of the adapted species also showed cross-adaptation, as shown by increased MICs of antibiotics and the other antiseptic. In most antiseptic-adapted bacteria, cell-surface hydrophobicity was increased and mass-spectrometry analysis revealed changes in expression of proteins involved in a wide range of functional domains. These in vitro data shows the adaptation and cross-adaptation of oral pathogens to antiseptics and antibiotics. This was related to changes in cell surface hydrophobicity and in expression of proteins involved in membrane transport, virulence, oxidative stress protection and metabolism

Adaptive pedestrian behaviour for the preservation of group cohesion

A crowd of pedestrians is a complex system in which individuals exhibit conflicting behavioural mechanisms leading to self-organisation phenomena. Computer models for the simulation of crowds represent a consolidated type of application, employed on a day-to-day basis to support designers and decision makers. Most state of the art models, however, generally do not consider the explicit representation of pedestrians aggregations (groups) and their implications on the overall system dynamics. This work is aimed at discussing a research effort systematically exploring the potential implication of the presence of groups of pedestrians in different situations (e.g. changing density, spatial configurations of the environment). The paper describes an agent-based model encompassing both traditional individual motivations (i.e. tendency to stay away from other pedestrians while moving towards the goal) and an adaptive mechanism representing the influence of group presence in the simulated population. The mechanism is designed to preserve the cohesion of specific types of groups (e.g. families and friends) even in high density and turbulent situations. The model is tested in simplified scenarios to evaluate the implications of modelling choices and the presence of groups. The model produces results in tune with available evidences from the literature, both from the perspective of pedestrian flows and space utilisation, in scenarios not comprising groups; when groups are present, the model is able to preserve their cohesion even in challenging situations (i.e. high density, presence of a counterflow), and it produces interesting results in high density situations that call for further observations and experiments to gather empirical data. The introduced adaptive model for group cohesion is effective in qualitatively reproducing group related phenomena and it stimulates further research efforts aimed at gathering empirical evidences, on one hand, and modelling efforts aimed at reproducing additional related phenomena (e.g. leader-follower movement patterns)