Smart house simulation based multi-agent system and internet of things

Zouai, Meftah; Kazar, Okba; Haba, Belgacem; Saouli, Hamza

doi:10.1109/mathit.2017.8259717

Cited by 14 publications

(8 citation statements)

References 8 publications

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“…Traditional user consumption is not flexible on a monthly basis. Smart meters and controllers can shift power demand from one month to the other with monthly rescheduling [17], [18]. To allow future smart rescheduling from those meters and controllers, here we propose a load shift model.…”

Section: B User's Energy Consumption Modelmentioning

confidence: 99%

A Reinforcement Learning-Based Decision System for Electricity Pricing Plan Selection by Smart Grid End Users

Chen

et al. 2021

IEEE Trans. Smart Grid

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Section: B User's Energy Consumption Modelmentioning

confidence: 99%

A Reinforcement Learning-Based Decision System for Electricity Pricing Plan Selection by Smart Grid End Users

Chen

et al. 2021

IEEE Trans. Smart Grid

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“…A multi-agent system is made of autonomous entities, with distributed information, computational capabilities, and possibly diverging interests. These kind of systems have been exploited in several fields: electronic [20] and industrial process control [3], economy [14], home automation [23], open system verification [1], to name a few. The way autonomous agents can interact with each other can be classified into two categories: competitive and cooperative.…”

Section: Introductionmentioning

confidence: 99%

The Parking Problem: A Game-Theoretic Solution

Calise¹,

Murano²,

Stranieri³

2022

Preprint

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In this paper, we propose a game-theoretic solution to the parking problem, by exploiting a strategic-reasoning approach for multi-agent systems. Precisely, cars are modeled by agents interacting among them in a multi-player game setting, whose aim is to get a free slot parking-place satisfying their own constraints. The overall assignment is then given as a Nash equilibrium solution. We come up with an algorithm (and its implementation in a tool) that works in quadratic time. We give evidence of the benefits of our approach by running our tool on a large hospital parking space.

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“…Multi-Agent Systems (MAS) are considered suitable tools for complex adaptive systems, especially for those that are distributed and dynamic, such as AmI [ 9 , 10 ]. Furthermore, the use of intelligent agents provides analysing information on distributed sensors [ 11 , 12 , 13 ]. These agents are capable of both independent reasoning and joint analysis of complex situations in order to achieve a high level of interaction with humans [ 14 ], enjoying all the characteristics of MAS systems of cooperation, organisation, and intelligence [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent Interaction to Assist Visually-Impaired and Elderly People

Oliveira

Engelmann

Kniest

et al. 2022

IJERPH

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A voice-controlled smart home system based on conversational agents can address the specific needs of older people, proactively providing support, compensating for cognitive decline, and coping with solitude, among other features. In particular, Multi-Agent Systems (MAS) platforms provide considerable support for complex adaptive systems that are naturally distributed and situated in dynamic environments, such as Ambient intelligence (AmI) applications. Such autonomous intelligent agents are capable of independent reasoning and joint analysis of complex situations to support high-level interaction with humans, besides providing typical characteristics of MAS, such as cooperation and coordinated action. In this context, we developed an approach using a MAS previously evaluated for visually impaired users, where most of the system’s functionalities are also helpful for the elderly. Our methodology is based on the four steps of the interactive design process. As a result, we determined that our approach has elements that allow for natural interaction with users, and we identified and discussed improvements and new features for future work. We believe that our findings can point to directions for building AmI systems that are capable of more natural interaction with users.

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Smart house simulation based multi-agent system and internet of things

Cited by 14 publications

References 8 publications

A Reinforcement Learning-Based Decision System for Electricity Pricing Plan Selection by Smart Grid End Users

A Reinforcement Learning-Based Decision System for Electricity Pricing Plan Selection by Smart Grid End Users

The Parking Problem: A Game-Theoretic Solution

Multi-Agent Interaction to Assist Visually-Impaired and Elderly People

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