An Introduction to MultiAgent Systems.

Two studies were conducted to examine whether shopping values are affected by perceived retail crowding, and whether shopping values mediate the relationship between perceived retail crowding and shopping satisfaction. Results of the first study show that perceived retail crowding affects shopping values, albeit not very strongly. However, the effects appear to be moderated by factors such as personal tolerance for crowding, time spent shopping, shopping intention, and whether a purchase was made. Study 2 indicates that the impact of perceived crowding on shopping value is mediated by emotions experienced by the shopper. The emotions and shopping value reactions, in turn, mediate the effect of spatial crowding on shopping satisfaction. Interestingly, the results show that when these mediating variables are accounted for, human crowding positively affects shopping satisfaction. These findings provide support for the inverted U explanation in the general crowding literature, and suggest new avenues of future research in the context of retail crowding.

Perceived retail crowding and shopping satisfaction: The role of shopping values

In the last few years, the number of papers devoted to applications of agent-based technologies to traffic and transportation engineering has grown enormously. Thus, it seems to be the appropriate time to shed light over the achievements of the last decade, on the questions that have been successfully addressed, as well as on remaining challenging issues. In the present paper, we review the literature related to the areas of agent-based traffic modelling and simulation, and agent-based traffic control and management. Later we discuss and summarize the main achievements and the challenges.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0269888913000118

A review on agent-based technology for traffic and transportation

Autonomous taxi (AT) fleets have the potential to take over a significant amount of traffic handled nowadays by conventionally driven vehicles (CDV). In this paper, we simulate a city-wide replacement of private cars with AT fleets of various sizes. The simulation model comprises microscopic demand for all private car trips in Berlin (including incoming and outgoing traffic), out of which the internal ones are exclusively served by ATs. The proposed real-time AT dispatching algorithm was optimized to handle hundreds of thousands of vehicles and millions of requests at low computing times. Simulation results suggest, that a fleet of 100 000 vehicles will be enough to replace the car fleet in Berlin at a high service quality for customers. Based on this, one AT could replace the demand served by ten CDVs in Berlin.

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Simulation of city-wide replacement of private cars with autonomous taxis in Berlin

This short review presents a selected history of the mutual fertilization between physics and economics, from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistic physics. Recent extensions in term of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it would not cover the dynamical field of agent based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the ``Emerging Market Intelligence hypothesis'' to reconcile the pervasive presence of ``noise traders'' with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models

The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status. The first part of the book gives an introduction to the most important concepts, with the intention of enabling a potential user to set up and run basic simulations. The second part of the book describes how the basic functionality can be extended, for example by adding schedule-based public transit, electric or autonomous cars, paratransit, or within-day replanning. For each extension, the text provides pointers to the additional documentation and to the code base. It is also discussed how people with appropriate Java programming skills can write their own extensions, and plug them into the MATSim core. The project has started from the basic idea that traffic is a consequence of human behavior, and thus humans and their behavior should be the starting point of all modelling, and with the intuition that when simulations with 100 million particles are possible in computational physics, then behavior-oriented simulations with 10 million travelers should be possible in travel behavior research. The initial implementations thus combined concepts from computational physics and complex adaptive systems with concepts from travel behavior research. The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. Another important aspect is the interpretation of the MATSim score as utility in the microeconomic sense, opening up a connection to benefit cost analysis. Finally, the book collects use cases as they have been undertaken with MATSim. All current users of MATSim were invited to submit their work, and many followed with sometimes crisp and short and sometimes longer contributions, always with pointers to additional references. We hope that the book will become an invitation to explore, to build and to extend agent-based modeling of travel behavior from the stable and well tested core of MATSim documented here.

The Multi-Agent Transport Simulation MATSim

This paper presents the application of the agent-based transport simulation toolkit MATSim-T to a large-scale scenario of Switzerland. The scenario is called large-scale because ca. 6 million synthetic persons, “agents”, are simulated on a high-resolution network model with >1 million links. MATSim-T is able to compute a relaxed state of the simulation system within 60 iterations of the learning-based solution procedure with regard to mode choice, car route choice and choice of activity timing. This is achieved by applying improved optimization algorithms in the replanning stage. A genetic algorithm is used for times and and mode choice optimization of activity plans, together with an efficient implementation of time-dependent shortest path search for route choice. The improvements of the behavioral model reported in this paper are focused on the scoring function which can process individualized parameters for measuring the quality of all-day activity plans. Combined with disaggregate input data for population and land use, it was possible to build a heterogeneous and thus more realistic scenario. Furthermore, four modes of transport (car, public transit, bike, walk) are considered in the presented application. The generalized cost of the car option is determined by a queue simulation of traffic flow. In order to prove the concept of mode choice optimization in a multi-agent microsimulation, the other modes are modelled as abstract alternatives with static travel costs constant throughout the modeled average workday. It is shown how the model is calibrated against observed modal split data. The results are validated with average workday count data. Despite the simple cost structure of the mode alternatives, and due to a mode choice concept based on subtours, the observed spatial distribution of the modal split can be reproduced within ±10 percentage points per mode.

Large-scale agent-based travel demand optimization applied to Switzerland, including mode choice

Travel surveys are increasingly taking advantage of GPS data, which offer precise route and time observations and a potentially reduced response burden. In these surveys, travel diaries are usually constructed automatically where research on the employed procedures has been focused on mode identification. The goal of the research reported here was to improve trip purpose identification. The analysis used random forests, a machine-learning approach that had been successfully applied to mode identification. The analysis was based on GPS tracks and accelerometer data collected by 156 participants who took part in a 1-week travel survey in Switzerland that was completed in 2012. The results show that random forests provide robust trip purpose classification. For ensemble runs, the share of correct predictions was between 80% and 85%. Different setups of the classifier were possible and sometimes required by the application context. The training set and its input variables (feature set) of the classifier were ...

Trip Purpose Identification from GPS Tracks

The activity-based multiagent simulation toolkit MATSim adopts a coevolutionary approach to capturing the patterns of people’s activity scheduling and participation behavior at a high level of detail. Until now, the search space of the MATSim system was formed by every agent’s route and time choice. This paper focuses on the crucial computational issues that have to be addressed when the system is being extended to include location choice. This results in an enormous search space that would be impossible to explore exhaustively within a reasonable time. With the use of a large-scale scenario, it is shown that the system rapidly converges toward a system’s fixed point if the agents’ choices are per iteration confined to local steps. This approach was inspired by local search methods in numerical optimization. The study shows that the approach can be incorporated easily and consistently into MATSim by using Hagerstrand’s time–geographic approach. This paper additionally presents a first approach to improving the behavioral realism of the MATSim location choice module. A singly constrained model is created; it introduces competition for slots on the activity infrastructure, where the actual load is coupled with time-dependent capacity restraints for every activity location and is incorporated explicitly into the agent’s location choice process. As expected, this constrained model reduces the number of implausibly overcrowded activity locations. To the authors’ knowledge, incorporating competition in the activity infrastructure has received only marginal attention in multiagent simulations to date, and thus, this contribution is also meant to raise the issue by presenting this new model.

Location Choice Modeling for Shopping and Leisure Activities with MATSim: Combining Microsimulation and Time Geography

This paper reports on the development of an agent-based cruising-for-parking simulation using the cellular automaton (CA) approach. The software was tested on a small-scale scenario, and a first verification step was performed for a real-world scenario for the town center of Zurich. Approaches to integrating the simulation into MATSim, a multi-agent transport simulation program, are discussed. The software is open source and can be downloaded from a free software repository. Empirical data that may be valuable for future model calibration are currently being surveyed in a global positioning system (GPS) study at the authors’ institute.

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Andreas Horni

Papers

The Multi-Agent Transport Simulation MATSim

Large-scale agent-based travel demand optimization applied to Switzerland, including mode choice

Trip Purpose Identification from GPS Tracks

Location Choice Modeling for Shopping and Leisure Activities with MATSim: Combining Microsimulation and Time Geography

An agent-based cellular automaton cruising-for-parking simulation