Artificial Intelligence Applied to Natural Resources Management

2010 ◽  
pp. 313-330
Author(s):  
Diana F. Adamatti ◽  
Marilton S. de Aguiar
Keyword(s):  
Artificial Intelligence ◽  
Data Analysis ◽  
Cellular Automata ◽  
Natural Resources ◽  
Natural Resources Management ◽  
Multi Agent Systems ◽  
Resources Management ◽  
Optimization And Control ◽  
Multi Agent ◽  
And Control

There are three computational challenges in natural resources management: data management and communication; data analysis; and optimization and control. The authors believe these three challenges can be dealt with Artificial Intelligence (AI) techniques, because they can manage dynamic activities in natural resources. There are several AI techniques such as Genetic Algorithms, Neural Networks, Multi-Agent Systems or Cellular Automata. In this chapter, the authors introduce some applications of Cellular Automata (CA) and Multi-Agent-Based Simulation (MABS) in natural resources management, because these are areas that the authors approach in their research and these areas can contribute to solve the three computational challenges. Specifically, the CA technique can face the challenge of data analysis because it can be extrapolated and new knowledge will be acquired from an area not known or experienced. Regarding the MABS technique, it can solve the challenge of optimization and control, because it works in an empiric way during the decision-making process, based on experiments and observations.

Artificial Intelligence Applied to Natural Resources Management

2012 ◽  
pp. 1566-1582 ◽  
Author(s):  
Diana F. Adamatti ◽  
Marilton S. de Aguiar
Keyword(s):  
Artificial Intelligence ◽  
Data Analysis ◽  
Cellular Automata ◽  
Natural Resources ◽  
Natural Resources Management ◽  
Multi Agent Systems ◽  
Resources Management ◽  
Optimization And Control ◽  
Multi Agent ◽  
And Control

There are three computational challenges in natural resources management: data management and communication; data analysis; and optimization and control. The authors believe these three challenges can be dealt with Artificial Intelligence (AI) techniques, because they can manage dynamic activities in natural resources. There are several AI techniques such as Genetic Algorithms, Neural Networks, Multi-Agent Systems or Cellular Automata. In this chapter, the authors introduce some applications of Cellular Automata (CA) and Multi-Agent-Based Simulation (MABS) in natural resources management, because these are areas that the authors approach in their research and these areas can contribute to solve the three computational challenges. Specifically, the CA technique can face the challenge of data analysis because it can be extrapolated and new knowledge will be acquired from an area not known or experienced. Regarding the MABS technique, it can solve the challenge of optimization and control, because it works in an empiric way during the decision-making process, based on experiments and observations.

Computational Techniques to Manage Natural Resources

2012 ◽  
Vol 3 (2) ◽  
pp. 117-137
Author(s):  
Diana F. Adamatti ◽  
Marilton S. de Aguiar
Keyword(s):  
Data Analysis ◽  
Natural Resources ◽  
Case Studies ◽  
Natural Resource ◽  
Life Quality ◽  
Natural Resources Management ◽  
Computational Techniques ◽  
Resources Management ◽  
Optimization And Control ◽  
And Control

To manage the natural resource, many aspect must be treat, because this are evolve all flora and fauna in planet. Mainly, how this management could improve the life quality in present and future, for all species (not just for human begins). In literature, there are three computational challenges in natural resources management: data management and communication; data analysis; and optimization and control. In this paper, the authors present four case studies where some techniques could help in the management of natural resources and to solve these challenges.

scholarly journals Water Resources Analysis: An Approach based on Agent-Based Modeling

2020 ◽  
Vol 27 (2) ◽  
pp. 81-95
Author(s):  
Giovani Farias ◽  
Bruna Leitzke ◽  
Míriam Born ◽  
Marilton Aguiar ◽  
Diana Adamatti
Keyword(s):  
Water Resources ◽  
Natural Resources ◽  
Agent Based Modeling ◽  
Natural Resources Management ◽  
Basin Modeling ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Resources Management ◽  
Agent Systems ◽  
Multi Agent

The paper aims to present a river basin modeling using GAMA platform for water resources analysis. Currently, several models based on multi-agent systems are used for natural resources management and they present satisfactory results for this type of scenario. GAMA is agents based and widely used in this context with several studies already published. In this study, the Sa ̃o Gonc ̧alo and Lagoa Mirim basins were considered from georeferenced data. In the modeling, regions, and rivers are agents on the system where rivers water can flow among neighbors regions.

scholarly journals Reports on the 2018 AAAI Spring Symposium Series

AI Magazine ◽  
2018 ◽  
Vol 39 (4) ◽  
pp. 29-35
Author(s):  
Christopher Amato ◽  
Haitham Bou Ammar ◽  
Elizabeth Churchill ◽  
Erez Karpas ◽  
Takashi Kido ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Well Being ◽  
Machine Intelligence ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Internet Of Everything ◽  
Symposium Series ◽  
Multi Agent ◽  
And Control

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University’s Department of Computer Science, presented the 2018 Spring Symposium Series, held Monday through Wednesday, March 26–28, 2018, on the campus of Stanford University. The seven symposia held were AI and Society: Ethics, Safety and Trustworthiness in Intelligent Agents; Artificial Intelligence for the Internet of Everything; Beyond Machine Intelligence: Understanding Cognitive Bias and Humanity for Well-Being AI; Data Efficient Reinforcement Learning; The Design of the User Experience for Artificial Intelligence (the UX of AI); Integrated Representation, Reasoning, and Learning in Robotics; Learning, Inference, and Control of Multi-Agent Systems. This report, compiled from organizers of the symposia, summarizes the research of five of the symposia that took place.

scholarly journals The Potential Role of the Artificial Intelligence in Combating Climate Change and Natural Resources Management: Political, Legal and Ethical Challenges

2021 ◽  
Vol 4 (3) ◽  
pp. 111-131
Author(s):  
Olena Lozo ◽  
Oleksii Onishchenko
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Natural Resources ◽  
Social Life ◽  
Early Stage ◽  
Legal Regulation ◽  
Natural Resources Management ◽  
Resources Management ◽  
The Impact

The aim of the article is to study the role of artificial intelligence (AI) in solving current issues of climate change, environmental protection and natural resources management. The advantages and threats of using AI for the development of political and legal parameters for ensuring the safe and effective implementation of technological system, as well as ensuring sustainable control over its functioning and development trends, are analyzed. The relevance of the topic is substantiated by the fact that the legislative basis in this area is at the early stage of formation, while the scale of the impact of AI on all the aspects of social life may be impossible to accurately foresee. A special attention is paid to the analysis of the legal regulation of these issues in the context of European Union and Ukraine. The present work is one of the few that addresses three issues: climate change, the growing influence of artificial intelligence, and the possibility of legal regulation of the use of AI to solve urgent environmental problems without threatening the fundamental human rights and freedoms.

Regional Policy in the Field of Natural Resources Management in the Far North

2003 ◽  
pp. 108-116
Author(s):  
A. Bykov
Keyword(s):  
Economic Development ◽  
Natural Resources ◽  
Regional Policy ◽  
Natural Resources Management ◽  
Economic Factors ◽  
Resource Saving ◽  
Resources Management ◽  
Legal Norms ◽  
Far North ◽  
The Russian Federation

According to the legal norms of the Russian Federation in the ownership, usage and disposal of natural resources the author analyses interaction between natural resources users and local authorities. The interaction is based upon ecological and economic factors, which cause the peculiarities of requirements put before natural resource users in the Far North. The strategic directions of resource saving economic development of these regions are considered.

Dynamic Generation and Control of Optimally Persistent Formation for Multi-agent Systems

2014 ◽  
Vol 39 (9) ◽  
pp. 1431-1438 ◽  
Author(s):  
Xiao-Yuan LUO ◽  
Shi-Kai SHAO ◽  
Xin-Ping GUAN ◽  
Yuan-Jie ZHAO
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Dynamic Generation ◽  
And Control
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