An architecture for modular distributed simulation with agent-based models

Agent-based simulations are an increasingly popular means of exploring and understanding complex social systems. In order to be useful, these simulations must capture a range of aspects of the modeled situation, each possibly requiring distinct expertise. Moreover, different paradigms may be useful in modelling, ranging from those that use many lightweight reactive agents, to those that use cognitive agents, to those that focus on agent teams and organisational structures. There is need for an architecture which supports the development of a large simulation, through the integration of separately developed modules. This paper describes a framework and architecture which facilitates the integration of multiple agent-based simulations into a single global simulation. This architecture naturally supports distributed simulation and incremental development, which are ways of addressing the computational and conceptual complexity of such systems. In this paper we focus particularly on how to ensure proper management of simulation data that is affected by agents in different modules, at the same logical time. We also provide some preliminary performance evaluation addressing scalability, as well as a comparison of how other available systems handle the issue of shared data

Expectation-Oriented Analysis and Design

A key challenge for agent-oriented software engineering is to develop and implement open systems composed of interacting autonomous agents. On the one hand, there is a need for permitting autonomy in order to support desirable system properties such as decentralised control. On the other hand, there is a need for restricting autonomy in order to reduce undesirable system properties such as unpredictability. This paper introduces a novel analysis and design method for open agent-oriented software systems that aims at coming up to both of these two contrary aspects. The characteristics of this method, called EXPAND, are as follows: (i) it allows agents a maximum degree of autonomy and restricts autonomous behaviour only if necessary (ii) it uses systemlevel expectations as a key modelling abstraction and as the primary level of analysis and design; and (iii) it is sociologically grounded in Luhmann's systems theory. The application of EXPAND is illustrated in a "car-trading platform" case study

Towards general cooperative game playing

Attempts to develop generic approaches to game playing have been around for several years in the field of Artificial Intelligence. However, games that involve explicit cooperation among otherwise competitive players cooperative negotiation games have not been addressed by current approaches. Yet, such games provide a much richer set of features, related with social aspects of interactions, which make them appealing for envisioning real-world applications. This work proposes a generic agent architecture Alpha to tackle cooperative negotiation games, combining elements such as search strategies, negotiation, opponent modeling and trust management. The architecture is then validated in the context of two different games that fall in this category Diplomacy and Werewolves. Alpha agents are tested in several scenarios, against other state-of-the-art agents. Besides highlighting the promising performance of the agents, the role of each architectural component in each game is assessed. (c) Springer International Publishing AG, part of Springer Nature 2018

Stress response function of a two-dimensional ordered packing of frictional beads

We study the stress profile of an ordered two-dimensional packing of beads in response to the application of a vertical overload localized at its top surface. Disorder is introduced through the Coulombic friction between the grains which gives some indeterminacy and allows the choice of one constrained random number per grain in the calculation of the contact forces. The so-called `multi-agent' technique we use, lets us deal with systems as large as $1000\times1000$ grains. We show that the average response profile has a double peaked structure. At large depth $z$, the position of these peaks grows with $cz$, while their widths scales like $\sqrt{Dz}$. $c$ and $D$ are analogous to `propagation' and `diffusion' coefficients. Their values depend on that of the friction coefficient $\mu$. At small $\mu$, we get $c_0-c \propto \mu$ and $D \propto \mu^\beta$, with $\beta \sim 2.5$, which means that the peaks get closer and wider as the disorder gets larger. This behavior is qualitatively what was predicted in a model where a stochastic relation between the stress components is assumed.Comment: 7 pages, 7 figures, accepted version to Europhys. Let

An Agent-Based Approach to Self-Organized Production

The chapter describes the modeling of a material handling system with the production of individual units in a scheduled order. The units represent the agents in the model and are transported in the system which is abstracted as a directed graph. Since the hindrances of units on their path to the destination can lead to inefficiencies in the production, the blockages of units are to be reduced. Therefore, the units operate in the system by means of local interactions in the conveying elements and indirect interactions based on a measure of possible hindrances. If most of the units behave cooperatively ("socially"), the blockings in the system are reduced. A simulation based on the model shows the collective behavior of the units in the system. The transport processes in the simulation can be compared with the processes in a real plant, which gives conclusions about the consequencies for the production based on the superordinate planning.Comment: For related work see http://www.soms.ethz.c