Modeling cooperative and competitive behaviors in emergency evacuation: A game-theoretical approach

A game-theoretical model to study evacuees’ cooperative and competitive behaviors during an emergency evacuation is proposed. The model integrated with evacuation dynamics model determines the density of cooperative and competitive evacuees and their related evacuation times. Computer simulation results show that (1) as urgency of evacuation increases, cooperation among evacuees’ decreases; (2) in an emergency situation, individual hyper-rationality among evacuees diminishes evacuation efficiency; (3) the imitation effect enhances cooperation among evacuees, yet reduces evacuation efficiency. This study provides a methodological pattern to research crowd behaviors in emergency evacuation.     

A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations

Many computational tools for the simulation and design of emergency evacuation and egress are now available. However, due to the scarcity of human and social behavioral data, these computational tools rely on assumptions that have been found inconsistent or unrealistic. This paper presents a multi-agent based framework for simulating human and social behavior during emergency evacuation. A prototype system has been developed, which is able to demonstrate some emergent behaviors, such as competitive, queuing, and herding behaviors. For illustration, an example application of the system for safe egress design is provided.     

A study on modeling of human spatial behavior using multi-agent technique

This research follows the design and implementation of an agent-based modeling environment written in Java program language on AnyLogic simulation platform to facilitate observing the human spatial behaviors of electric taxis and passengers. The system is developed with a view to improve decision analysis and support for users or companies. In order to achieve the object of decision support for the user, we provide a graphic user interface (GUI) to support user making decision real time. User can simulate the real condition via GUI in our electric taxi DAR operation system to observe the simulation process and the result to help reasonable decision-making immediately. We validate our multi-agent simulation model with the electric taxi DAR operation system case study. Finally, according to the analysis result, we demonstrate that our multi-agent simulation model and GUI can help users or companies quickly make a quality and accurate decision to reduce the decision-making cost and time. In this condition, users or companies can strengthen their competitive advantage and response ability with the reduction of decision-making risk.     

A multi-agent approach for integrated emergency vehicle dispatching and covering problem

The most important decisions that should be made by emergency vehicle managers are related to the allocation and the covering problems. The allocation (or dispatching) problem consists of deciding which vehicle must be assigned to assist an emergency in the best times. The covering problem aims at keeping the region under surveillance well-covered by relocating available vehicles. As components are geographically distributed, decentralized solution approaches may present several advantages. This paper develops a decentralized distributed solution approach based on multi-agent systems (MAS) to manage the emergency vehicles. The proposed system integrates the dispatching of vehicles to calls with zone coverage issues. This integration means that allocation and covering decisions are considered jointly. The idea of MAS has been applied in many others real-world contexts, and has been proven to provide more flexibility, reliability, adaptability and reconfigurability. To our knowledge, there is no existing work that uses MAS for real-time emergency vehicle allocation problem while accounting for the coverage requirements for future demands. We propose a multi-agent architecture that fit the real emergency systems, and that aims at keeping good performance compared to the centralized solution. The objective is to coordinate agents to reach good quality solutions in a distributed way. For this purpose two approaches are examined. The first one is used to show the impact of distributing data and control on the solution quality, since the dispatching decisions are based only on local evaluations of the fitness. The second approach is based on implicit agents' coordination using a more refined and efficient auction mechanism. The performance of each approach is compared to the centralized solution obtained by solving the proposed model with ILOG CPLEX solver. The obtained results show the importance of the coordination method to keep a good quality of service while distributing data and decision making, and prove the performance of the second approach.     

A review of behavior mechanisms and crowd evacuation animation in emergency exercises

Emergency exercises are an efficient approach for preventing serious damage and harm, including loss of life and property and a wide range of adverse social effects, during various public emergencies. Among various factors affecting the value of emergency exercises, including their design, development, conduct, evaluation, and improvement planning, this paper emphasizes the focal role of evacuees and their behavior. We address two concerns: What are the intrinsic reasons behind human behavior? How do we model and exhibit human behavior? We review studies investigating the mechanisms of psychological behavior and crowd evacuation animation. A comprehensive analysis of logical patterns of behavior and crowd evacuation is presented first. The interactive effects of information (objective and subjective), psychology (panic, small groups, and conflicting roles), and six kinds of behavior contribute to a more effective understanding of an emergency scene and assist in making scientific decisions. Based on these studies, a wide range of perspectives on crowd formation and evacuation animation models is summa- rized. Collision avoidance is underlined as a special topic. Finally, this paper highlights some of the technical challenges and key questions to be addressed by future developments in this rapidly developing field.     

Escape behavior in factory workshop fire emergencies: a multi-agent simulation

In this study, a multi-agent simulation is conducted to explore the relationship between fire escape survival rate and occupants’ risk preferences and stress capacity. The results indicate that, the escape survival rates for occupants with different risk preferences and stress capacities can be significantly different. More specifically, the simulation shows that the smaller the number of occupants is in a fire, the higher the survival rate can be expected. In addition, the simulation shows that the larger the number of individuals with stronger stress capacities is in a group, the higher the escape survival rate the group has. Moreover, the simulation shows that the more disperse the individuals’ risk preferences is in a group, the higher the escape survival rate the group has. Based on the simulation results, the paper proposes a framework of E-evacuation system to guide the rational escape and evacuation when enterprise workshop fire occurs. Suggestions for increasing escape survival rates during fires are provided.     

PLANGENT: an approach to making mobile agents intelligent

Network environments give computer users the option of employing distributed information and services to complete a task. However, gathering information and using services distributed in networks requires knowing exactly what kinds of information and services are required for a task, where they are, and how they can be obtained or utilized. Tracking down the answers to these questions can be difficult, time consuming tasks for users. Mobile agent technology is expected to release them from having to do so. Instead, “intelligent” mobile agents will comprehend the user's requirements, search network nodes autonomously for appropriate information and services, and return with the answers. But several problems must be solved before we can expect agents to perform such actions effectively. We focus on the question of intelligence as a prerequisite for agent functions. What sort of intelligence is expected of agents? We have adopted a model based on the ability to make flexible plans. Specifically, we think mobile agents must be able to: understand user requirements; plan actions that will satisfy the requirements act according to the plan; modify the plan according to actual conditions when they differ from those initially expected; and execute the modified plan. We have implemented these functions in the Plangent system and validated their effectiveness in several example applications. We describe how we combined these planning functions with mobile agent facilities, and show how the agents behave intelligently in an example application of personal travel assistance     

Modeling human eye behavior during mammographic scanning:preliminary results

We investigate the use of an inexpensive and unobtrusive eye-tracking system to explore relationships between visual scanning patterns, pupillary response, and the clinical diagnoses of mammographic experts. One radiologist and three radiological technicians each examined a series of 14 mammograms for indications of abnormalities associated with breast cancer. The status of each mammogram was verified by biopsy. The eye-tracking system was used to measure and record eye position and pupil diameter as a function of time as the subjects scanned the mammograms. Three treatments were applied to the scan data to model the experts' eye behaviors. These included quantification of dwell time and pupil diameter as a function diagnostic accuracy in regions of the mammogram where abnormalities existed or were perceived; independent clustering of lookpoints without respect to abnormalities; and analysis of scan transitions between lookpoint clusters. Results of the analysis were consistent with extensive prior studies of eye-scan measures recorded during the diagnosis of abnormalities on chest radiograms. This preliminary investigation provides a proof of concept for use of the eye-tracking technology, experimental protocols, and analysis methodologies as the basis for expanded mammographic studies, with the promise of eventual adaptation as a source of diagnostic information in clinical practice     

Modeling self-efficacy in intelligent tutoring systems: An inductive approach

Self-efficacy is an individual’s belief about her ability to perform well in a given situation. Because self-efficacious students are effective learners, endowing intelligent tutoring systems with the ability to diagnose self-efficacy could lead to improved pedagogy. Self-efficacy is influenced by (and influences) affective state. Thus, physiological data might be used to predict a student’s level of self-efficacy. This article investigates an inductive approach to automatically constructing models of self-efficacy that can be used at runtime to inform pedagogical decisions. It reports on two complementary empirical studies. In the first study, two families of self-efficacy models were induced: a static self-efficacy model, learned solely from pre-test (non-intrusively collected) data, and a dynamic self-efficacy model, learned from both pre-test data as well as runtime physiological data collected with a biofeedback apparatus. In the second empirical study, a similar experimental design was applied to an interactive narrative-centered learning environment. Self-efficacy models were induced from combinations of static and dynamic information, including pre-test data, physiological data, and observations of student behavior in the learning environment. The highest performing induced naïve Bayes models correctly classified 85.2% of instances in the first empirical study and 82.1% of instances in the second empirical study. The highest performing decision tree models correctly classified 86.9% of instances in the first study and 87.3% of instances in the second study.     

Crowd simulation for emergency response using BDI agents based on immersive virtual reality

This paper presents a novel methodology involving a Virtual Reality (VR)-based Belief, Desire, and Intention (BDI) software agent to construct crowd simulation and demonstrates the use of the same for crowd evacuation management under terrorist bomb attacks in public areas. The proposed BDI agent framework allows modeling of human behavior with a high degree of fidelity. The realistic attributes that govern the BDI characteristics of the agent are reverse-engineered by conducting human-in-the-loop experiments in the VR-based Cave Automatic Virtual Environment (CAVE). To enhance generality and interoperability of the proposed crowd simulation modeling scheme, input data models have been developed to define environment attributes (e.g., maps, demographics, evacuation management parameters). The validity of the proposed data models are tested with two different evacuation scenarios. Finally, experiments are conducted to demonstrate the effect of various crowd evacuation management parameters on the key performance indicators in the evacuation scenario such as crowd evacuation rate and densities. The results reveal that constructed simulation can be used as an effective emergency management tool.     

On-demand e-supply chain integration: A multi-agent constraint-based approach

With e-business emerging as a key enabler to drive supply chains, the focus of supply chain management has been shifted from production efficiency to customer-driven and partnership synchronization approaches. This strategic shift depends on the match between the demands and offerings that deliver the services. To achieve this, we need to coordinate the flow of information among the services, and link their business processes under various constraints. Existing approaches to this problem have relied on complete information of services and resources, and have failed to adequately address the dynamics and uncertainties of the operating environments. The real-world situation is complicated as a result of undetermined requirements of services involved in the chain, unpredictable solutions contributed by service providers, and dynamic selection and aggregation of solutions to services. This paper examines an agent-mediated approach to on-demand e-business supply chain integration. Each agent works as a service broker, exploring individual service decisions as well as interacting with each other for achieving compatibility and coherence among the decisions of all services. Based on the framework, a prototype has been implemented with simulated experiments highlighting the effectiveness of the approach.     

Evolving intelligent agents: A 50 year quest

Already in the early 1960s, Larry Fogel and his colleagues were exploring the possibility of creating artificial intelligence using simulated evolution. Over the past 50 years, that idea has captured the imagination of many people and has led to a wide variety of approaches. In this article, this quest is summarized, the current state of the art is described, and some of the remaining open questions are discussed.     

A model of agents (robots) command behavior: The cognitive approach

The paper suggests a mathematical model of agents’ cooperation in dynamics, which employs agents’ utility functions and cognitive dissonance of their relations. The model is based on the theories of social psychologists investigating the behavior of people in small social groups and explaining the principles of their functioning and stability. We illustrate the suggested model via simulation of virtual soccer game of agents (robots). The performed simulation allows to model diverse aspects of agents’ cooperation and selfish behavior.     

Finite-time multi-agent deployment: A nonlinear PDE motion planning approach

The systematic flatness-based motion planning using formal power series and suitable summability methods is considered for the finite-time deployment of multi-agent systems into planar formation profiles along predefined spatial–temporal paths. Thereby, a distributed-parameter setting is proposed, where the collective leader–follower agent dynamics is modeled by two boundary controlled nonlinear time-varying PDEs governing the motion of an agent continuum in the plane. The discretization of the PDE model directly induces a decentralized communication and interconnection structure for the multi-agent system, which is required to achieve the desired spatial–temporal paths and deployment formations.     

Modeling,simulation and analysis of aircraft arresting system using bond graph approach

Aircraft arrester systems are used to arrest the incoming aircrafts in case of emergency landing and aborted take off situations. This paper presents an approach for modeling, simulation and analysis of aircraft arresting system using bond graphs for electronically controlled, hydraulically operated multi disc friction type of braking arrangement. A detailed dynamic model of the aircraft arrester system is modeled through bond graphs in which the various sub-systems of the total system are created as capsules (sub-system objects). Detailed analysis for each of these sub-systems is carried out and then final results are obtained. The simulation is carried out for different aircraft weights and landing speeds.     

Unplanned effects of intelligent agents on Internet use: a social informatics approach

This paper instigates a discourse on the unplanned effects of intelligent agents in the context of their use on the Internet. By utilizing a social informatics framework as a lens of analysis, the study identifies several unanticipated consequences of using intelligent agents for information- and commerce-based tasks on the Internet. The effects include those that transpire over time at the organizational level, such as e-commerce transformation, operational encumbrance and security overload, as well as those that emerge on a cultural level, such as trust affliction, skills erosion, privacy attrition and social detachment. Furthermore, three types of impacts are identified: economic, policy, and social. The discussion contends that economic impacts occur on the organizational level, social effects transpire on a cultural level, and policy impacts take place on both levels. These effects of the use of intelligent agents have seldom been predicted and discussed by visionaries, researchers, and practitioners in the field. The knowledge of these unplanned outcomes can improve our understanding of the overall impacts that innovative agent technologies may potentially have on organizations and individuals. Subsequently, this may help us develop better agent applications, facilitate the formulation of appropriate contingencies, and provide impetus for future research.     

Modeling emergency evacuation of individuals with disabilities (exitus): An agent-based public decision support system

In this paper, we present a public decision support system (DSS) distinguished from various DSSs in the private business sector in terms of its ownership, data scarcity, and beneficiaries. In particular, our system is intended to play a vital role in assessing and optimizing emergency response plans for rare but catastrophic events such as the September 11th attacks. While taking an agent-based microscopic simulation approach in a hierarchical framework, we used our model to estimate the effectiveness of alternative evacuation strategies to support emergency response planning as a part of business continuity planning for all private business organizations. The presented model is unique because it considers individuals with disabilities explicitly in terms of speed, ability to negotiate the environment, and normalcy bias depending on type of disability. It is also capable of classifying the environment in terms of accessibility characteristics encompassing various conditions which have been shown to have a disproportionate effect upon the behavior of individuals with disabilities during an emergency.Through a series of simulation experiments, our system identified specific locations (e.g., the NW landing) on the 3rd floor of the test bed building as possible bottleneck spots under certain conditions (e.g., the sharp increase in individuals with disabilities among residents). This way, our system provides the architect with tools to test the structure’s design to determine how well it meets the identified requirements for emergency evacuation to accommodate this shifting demographic. In particular, our system strongly demonstrated the effectiveness of new emergency evacuation strategies for individuals with disabilities such as assisted evacuations which allows other healthy people to play more active roles compared to traditional strategies in which individuals with disabilities are helplessly waiting for assistants such as fire fighters at the designated area. Our system also revealed that people using wheelchairs and those with lower stamina were at the greatest risk. People with lower stamina such as the elderly, people with chronic health conditions, or those with temporary injuries are at a greater risk mainly because they are not easily identifiable. Ultimately, the proposed DSS system can be used to inform public policy professionals of more effective, evidence-based evacuation planning and environmental design methods based on a better understanding of the behavior of individuals with disabilities.     

A multi-agent approach using perceptron-based learning for robust operation of distributed chemical reactor networks

Controlling the individual reactors of a chemical reactor network producing different grades of a product requires intelligent reconfiguration strategies. Agent-based approaches are ideal for such distributed manufacturing processes, since they provide flexible, robust, and emergent solutions under dynamically changing process conditions. This paper proposes a multi-layered, multi-agent framework based on a decentralized online learning approach for the supervision of grade transitions in autocatalytic reactor networks. The values for the manipulated variables and the path to the target reactor are determined to give the least disturbance to the system. Case studies illustrate the performance of the approach in managing grade transition and disturbance rejection in a reactor network.