Search results for "Multi-Agent System"

Modelling PM10 Crisis Peaks Using Multi-agent Based Simulation: Application to Annaba City, North-East Algeria

2015

The paper describes a MAS (multi-agent system) simulation approach for controlling PM10 (Particulate Matter) crisis peaks. A dispersion model is used with an Artificial Neural Network (ANN) to predict the PM10 concentration level. The dispersion and ANN models are integrated into a MAS system. PM10 source controllers are modelled as software agents. The MAS is composed of agents that cooperate with each other for reducing their emissions and control the air pollution peaks. Different control strategies are simulated and compared using data from Annaba (North-East Algeria). The simulator helps to compare and assess the efficiency of policies to control peaks in PM10.

Evolutionary Game Dynamics for Collective Decision Making in Structured and Unstructured Environments

2017

Abstract For a large population of players we consider a collective decision making process with three possible choices: option A or B or no option. The more popular option is more likely to be chosen by uncommitted players and cross-inhibitory signals can be sent to attract players committed to a different option. This model originates in the context of honeybees swarms, and we generalise it to accommodate other applications such as duopolistic competition and opinion dynamics. The first contribution is an evolutionary game model and a corresponding new game dynamics called expected gain pairwise comparison dynamics explaining how the strategic behaviour of the players may lead to deadlock…

A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics

2006

We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.

Reinforcement Learning Your Way: Agent Characterization through Policy Regularization

2022

The increased complexity of state-of-the-art reinforcement learning (RL) algorithms has resulted in an opacity that inhibits explainability and understanding. This has led to the development of several post hoc explainability methods that aim to extract information from learned policies, thus aiding explainability. These methods rely on empirical observations of the policy, and thus aim to generalize a characterization of agents’ behaviour. In this study, we have instead developed a method to imbue agents’ policies with a characteristic behaviour through regularization of their objective functions. Our method guides the agents’ behaviour during learning, which results in a…

An MAS-based subjective model for indoor adaptive thermal comfort

2015

The achievement of high level personalized sets of comfort parameters is contemplated within the more general context of the so-called smart buildings, where people, by means of the new communication technologies, become active actors to the process of the singling out and control of the best indoor conditions. This Dynamic Intelligence approach would usefully contribute to a better energy efficient and environmental friendly management of buildings. Multi-Agent schemes are suitable tools in this aim, since they are able to manage the user-building-plant system where the adaptivity of people to the indoor conditions is suitably achieved. In this paper a contribution to a development of the …

Human-Robot Teaming Interaction: a Cognitive Architecture Solution

2021

Computer Mediated Communication and Collaboration in a Virtual Learning Environment Based on a Multi-agent System with Wasp-Like Behavior

2008

In this paper is presented a model for an adaptive multi-agent system for dynamic routing of the grants' activities from a learning environment, based on the adaptive wasp colonies behavior. The agents use wasp task allocation behavior, combined with a model of wasp dominance hierarchy formation. The model we introduced allows the assignment of activities in a grant, taking into account the specialization of students, their experience and the complexity of activities already taken. An adaptive method allows students to enter in the Grant system for the first time. The system is changing dynamic, because both the type of activities and the students involved in the system change. Our approach…

A Stigmergic Guiding System to Facilitate the Group Decision Process

2012

The paper presents a stigmergic approach to engineer a guiding system to facilitate the complex problem of designing the group decision processes. The system aims to provide contextual, actionable recommendations based on the knowledge and past experience of its users as recorded in a collaborative working environment implemented around the concept of stigmergic systems. Through an agent-based socio-simulation experiment we have demonstrated already the feasibility of this approach. The paper illustrates how the simulation results are transferred into a guiding system that facilitates the group decision process design through iterative queries reformulations for the identification, represen…

Computing Real-Time Dynamic Origin/Destination Matrices from Vehicle-to-Infrastructure Messages Using a Multi-Agent System

2012

Dynamic Origin/Destination matrices are one of the most important parameters for efficient and effective transportation system management. These matrices describe the vehicle flow between different points within a region of interest for a given period of time. Usually, dynamic O/D matrices are estimated from traffic counts provided by induction loop detectors, home interview and/or license plate surveys. Unfortunately, estimation methods take O/D flows as time invariant for a certain number of intervals of time, which cannot be suitable for some traffic applications. However, the advent of information and communication technologies (e.g., vehicle-to-infrastructure dedicated short range comm…

Distributed image retrieval on DAISY

2006

The paper describes an application of image retrieval based on DAISY architecture (distributed architecture for intelligent system). The creation of pictorial indexes may require a number of hours depending on the size of the pictorial data base. The problem can become more complex in the case of distributed database systems. In both cases a distributed architecture can be the natural and more efficient solution. DAISY architecture is based on the concept of co-operating behavioral agents supervised by a central engagement module. Preliminary experiments, to evaluate the performance of the system, have been performed on a astronomical database and coral image