Guy Camilleri

A Recommender System Based on Multi-Criteria Aggregation

Recommender systems aim to support decision-makers by providing decision advice. We offer multi-criteria decision recommendations based on a performance matrix and a partial order on criteria submitted by the user. Our method is to aggregate performance measures over all criteria based on inferences about preferences from the decision-maker’s input. After reviewing some multicriteria aggregation operators, we present a recommender system that uses the Choquet integral of a fuzzy measure to determine a total ordering of the alternatives.

Principle and evaluation of a self-Adaptive Multi-Agent System for State Estimation of electrical distribution network

In our daily life, electricity becomes more and more important. Mainly for environmental concerns, governments tend to encourage integration of generators which rely on renewable energy sources. Therefore, it is necessary to move from present electrical networks to smarter ones. These issues have contributed to the development of the concept of Smart Grid. One might well ask the question: how to add a layer of intelligence on electrical networks as we know them? The work presented in this paper is mainly focused on the State Estimation as a way to observe the evolution of low voltage or medium voltage disturbances in order to mitigate them using innovative regulation functions. The Atena platform presented in this study has shown the feasibility and some advantages of using an adaptive multi-agent system for the estimation of the network state within a reasonable time, with encouraging accuracy for voltage regulation, with a linear complexity and with the capacity to adapt itself to changes that can occur in the network. Each agent has only a local perception of the grid and interacts with its immediate neighbors according to the network topology, without any information on the global state.

Dynamic Models for Ideas Number Prediction in Brainstorming

In this paper, we extend the approach presented in [1] to the cognitive model of brainstorming proposed by Brown and Paulus in [4]. In their work Brown and Paulus developed two dynamic models of brainstorming, a non-cognitive model and a cognitive model. These models describe for each participant, the evolution of ideas number over time, and are formalized by differential equations. Through solution functions of these models, we propose to calculate the number of ideas of each participant on any time intervals and thus in the future (called prediction). To enable computing solution functions, we used an optimization model to determine the model parameter values. In this paper, we propose an optimization model based on the fourth order Runge-Kuttas numerical method and we apply it to the cognitive model. Through some feasibility tests, we show the adequacy of the proposed approach to our prediction context.

A timing management banner for supporting group decision making

Time Management stays a major problem to be considered in group decision making processes. In this paper we propose a prototype banner in order support the facilitator involved in a group decision making processes. This prototype has for objective to advertise members of the group of the time consuming.

Electric Vehicles Fleet for Frequency Regulation Using a Multi-Agent System

The production of PhotoVoltaic (PV) energy depends on the solar irradiance level. The PV power plant fluctuations may have a significant impact on the frequency regulation in sufficiently small power systems, such as islands. The objective of this paper is to present a method using cooperative multi-agent systems to reduce the frequency fluctuations due to the unpredicted fluctuations of the PV production using electric vehicles as electricity storage units in an isolated power system.

A Mixed Usability Evaluation on a Multi Criteria Group Decision Support System in Agriculture

Decision Support Systems (DSS) help users make decisions by organizing the decision-making process in stages, dealing with several input sources. In the agricultural context, these tools are becoming more important given the variety of data that producers face, market regulations and interaction of several actors with different backgrounds. Different DSS have existed for years, but their adoption is reportedly very low, being poor usability one of the most relevant factors. While there are surveys indicating this, we have not found usability evaluations on DSS with concrete results. In this work, we evaluated decision-making in the agricultural domain using a group DSS called GRUS. We present 3 different usability evaluations: a heuristic evaluation, a user test, and an automated diagnosis.

A Volunteer Design Methodology of Data Warehouses

In the context of Volunteered Geographic Information (VGI), volunteers are not involved in the decisional processes. Moreover, VGI systems do not offer advanced historical analysis tools. Therefore, in this work, we propose to use Data Warehouse (DW) and OLAP systems to analyze VGI data, and we define a new DW design methodology that allows involving volunteers in the definition of analysis needs over VGI data. We validate it using a real biodiversity case study.

Principles and Experiments of a Multi-Agent Approach for Large Co-Simulation Networks Initialization.

Simulating large systems, such as smart grids, often requires to build a network of specific simulators. Making heterogeneous simulators work together is a challenge in itself, but recent advances in the field of co-simulation are providing answers. However, one key problem arises, and has not been sufficiently addressed: the initialization of such networks. Many simulators need to have proper input values to start. But in the network, each input is another simulator’s output. One has to find the initial input values of all simulators such as their computed output is equal to the initial input value of the connected simulators. Given that simulators often contain differential equations, this is hard to solve even with a small number of simulators, and nearly impossible with a large number of them. In this paper, we present a mutli-agent system designed to solve the co-simulation initialization problem, and show preliminary results on large networks.

Multi-criteria Group Decision Making with Private and Shared Criteria: An Experiment

Collective decision processes remain a common management approach in most organizations. In such processes, it seems important to offer participants the opportunity to confront the differences in their points of view. To this end, cognitive and technical tools are required that facilitate the sharing of individuals’ reasoning and preferences, but at the same time allow them to keep some information and attitudes to themselves. The aim of our study is to assess whether, in the multi-criteria approach to problem structuring, decision-makers can be comfortable using shared criteria in addition to private criteria. For this purpose, an exploratory experiment with student subjects was conducted using the Group Decision Support System, GRUS.

Self-adaptive Distribution System State Estimation

Electricity plays an increasingly important role in our society. Indeed, we are moving toward the era of “everything electric”. The needs evolving, it is mandatory to rethink the way electricity is produced and distributed. This then introduces the concept of an autonomous and intelligent power system called the Smart Grid.