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Applications of self-organising multi-agent systems: an initial framework of comparison. Informatica
, 2005
"... A lot of work is devoted to formalizing and devising architectures for agents ' cooperative behaviour, for coordinating the behaviour of individual agents within groups, as well as to designing agent societies using social laws. However, providing agents with abilities to automatically devise s ..."
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A lot of work is devoted to formalizing and devising architectures for agents ' cooperative behaviour, for coordinating the behaviour of individual agents within groups, as well as to designing agent societies using social laws. However, providing agents with abilities to automatically devise societies so as to form coherent emergent groups that coordinate their behaviour via social laws, is highly challenging. These systems are called self-organised. We are beginning to understand some of the ways in which selforganised agent systems can be devised. In this perspective, this paper provides several examples of multi-agent systems in which self-organisation, based on different mechanisms, is used to solve complex problems. Several criteria for comparison of self-organisation between the different applications are provided. Povzetek: Članek opisuje primere in kriterije samoorgarnizacije v agentnih sistemih. 1
Interaction Biases in Multi-Agent Simulations: An Experimental Study
"... Abstract. How to ensure that two different implementations of a sim-ulation will produce the same results? In order to assure simulation reproducibility, some domain-independent functional unit must be pre-cisely described. We show in this paper that the management unit that rules the participation ..."
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Abstract. How to ensure that two different implementations of a sim-ulation will produce the same results? In order to assure simulation reproducibility, some domain-independent functional unit must be pre-cisely described. We show in this paper that the management unit that rules the participation of an agent in simultaneous interactions is one of them. Usually, many choices concerning this unit are made implicitly, even if they might lead to many simulation biases. We illustrate this issue through a study of biases that appear even in simple cases, due to a specification lack, and we propose as a solution a classification of interactions that makes those choices explicit. 1
Holonic Modeling of Environments for Situated Multi-Agent Systems
"... Abstract. In a Multi-Agent Based Simulation (MABS) special atten-tion must go to the analysis, modeling and implementation of the en-vironment. Environments for simulation of real world problems may be complex. Seeing the environment as a monolithic structure only reduces our capacity to handle larg ..."
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Abstract. In a Multi-Agent Based Simulation (MABS) special atten-tion must go to the analysis, modeling and implementation of the en-vironment. Environments for simulation of real world problems may be complex. Seeing the environment as a monolithic structure only reduces our capacity to handle large scale, real-wold environments. In order to support this type of environments, we propose the use of an holonic per-spective to represent the environment and the agents. In our approach, agents and environment are represented by holons. The environment de-fines an holarchy. Agents belong to a specific holon in this holarchy fol-lowing their needs. Key words: holonic modeling, environment of MAS, simulation 1
Multi-level agent-based modeling with the Influence Reaction principle
"... This paper deals with the specification and the implementation of multi-level agent-based models, using a formal model, IRM4MLS (an In-fluence Reaction Model for Multi-Level Simulation), based on the Influ-ence Reaction principle. Proposed examples illustrate forms of top-down control in (multi-leve ..."
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This paper deals with the specification and the implementation of multi-level agent-based models, using a formal model, IRM4MLS (an In-fluence Reaction Model for Multi-Level Simulation), based on the Influ-ence Reaction principle. Proposed examples illustrate forms of top-down control in (multi-level) multi-agent based-simulations.
unknown title
, 2011
"... Integrated methodological frameworks for modeling agent-based advanced supply chain planning systems: A systematic literature review ..."
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Integrated methodological frameworks for modeling agent-based advanced supply chain planning systems: A systematic literature review
INTEGRATING AGENT BASED MODELING INTO A DISCRETE EVENT SIMULATION The benefits of Discrete Event Simulation (DES) are well
"... Movement of entities in discrete event simulation typically requires predefined paths with decision points that dictate entity movement. Human-like travel is difficult to model correctly with these constraints because that is not how people move and large individual differences exist in capabilities ..."
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Movement of entities in discrete event simulation typically requires predefined paths with decision points that dictate entity movement. Human-like travel is difficult to model correctly with these constraints because that is not how people move and large individual differences exist in capabilities and strategies. Agent based modeling is considered a better way to simulate the real-time interaction of people with their environment. In this paper we propose to integrate agent based modeling with discrete event simulation to simulate the movement of people in a discrete event system. An agent based module was constructed within the AutoMod simulation package, and a test case was modeled in which people (agents) at a theme-park interact with objects and people in their environment to get directions and
A Methodology to Engineer and Validate Dynamic Multi-level Multi-agent Based Simulations Jean-Baptiste Soyez1,2
"... This article proposes a methodology to model and simulate complex systems, based on IRM4MLS, a generic agent-based meta-model able to deal with multi-level systems. This methodology permits the engineering of dynamic multi-level agent-based models, to represent complex systems over several scales an ..."
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This article proposes a methodology to model and simulate complex systems, based on IRM4MLS, a generic agent-based meta-model able to deal with multi-level systems. This methodology permits the engineering of dynamic multi-level agent-based models, to represent complex systems over several scales and domains of interest. Its goal is to simulate a phenomenon using dynamically the lightest representation to save computer resources without loss of information. This methodology is based on two mechanisms: (1) the activation or deactivation of agents representing different domain parts of the same phenomenon and (2) the aggregation or disaggregation of agents representing the same phenomenon at different scales. 1
Timing matters: Lessons From The CA Literature On Updating
"... Abstract. In the present article we emphasize the importance of modeling time in the context of agent-based models. To this end, we present a (selective) survey of the Cellular Automata-literature on updating and draw parallels to the issue of agent activation in agent-based models. By means of two ..."
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Abstract. In the present article we emphasize the importance of modeling time in the context of agent-based models. To this end, we present a (selective) survey of the Cellular Automata-literature on updating and draw parallels to the issue of agent activation in agent-based models. By means of two simple models, Schelling’s segregation model and Epstein’s demographic prisoner’s dilemma we investigate the influence of choosing different regimes of agent activation. Our experiments indicate that timing is not a critical issue for very simple models but bears huge influence on model behavior and results as soon as the degree of complexity increases only so slightly. After a brief review of the way commonly used ABM simulation environments handle the issue of timing, we draw some tentative conclusions about the importance of timing and the need for more research towards that direction, similar to the concerted effort on updating in cellular automata.
systems—Multi-Agent Based Simulation General Terms
"... The IRM4S model (Influence Reaction Model for Simula-tion) is an adaptation of the formalism of [2] for multi-agent based simulations (MABS). The goal of IRM4S is to provide a framework that eases the use of the Influence/Reaction principle within MABS. ..."
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The IRM4S model (Influence Reaction Model for Simula-tion) is an adaptation of the formalism of [2] for multi-agent based simulations (MABS). The goal of IRM4S is to provide a framework that eases the use of the Influence/Reaction principle within MABS.
unknown title
, 2011
"... Integrated methodological frameworks for modeling agent-based advanced supply chain planning systems: A systematic literature review ..."
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Integrated methodological frameworks for modeling agent-based advanced supply chain planning systems: A systematic literature review