++ We have taken down all the Kindle booklets on 31 Dec 2021 in order to pursue a different path, with software coming first. The booklets will return at a later stage!
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Literature Review: Operations Research problem for Artificial Intelligence
This “Ten Problems for Artificial Intelligence in the 2020s” booklet identifies ten relevant areas from very recent contributions put forward at academic level in the form journal articles, conference proceedings and students theses. Ten freely accessible internet references have been selected for each area and direct links are provided at the end of each chapter for own consultation. Our selected references do not intend to mirror ranking indexes nor establish novel classifications. On the contrary, they are meant to represent peer-reviewed, diverse and scientifically-sound case studies for vertical dissemination aimed at non-specialist readers. They will also be able to scoop even more references through the bibliography that is reported at the end of each selected reference.
Without further ado, these are the ten problems that we are going to introduce in this booklet:
- computer games,
- intelligent optimization,
- human intervention,
- ethical issues,
- software development,
- open source,
- operations research.
Each problem has its own dedicated chapter made of an introductory section, a short presentation of the ten selected references and a conclusions section.
The final chapter of this booklet will report the conclusions from each chapter again in order to provide a complete executive summary.
10 Operations Research
THE PROBLEM — Many artificial intelligence problems are Operations Research (OR) problems. How to play the role of fundamental subject has become a topic of concern in military operations research. Using new technologies, adopting new approaches or applying OR methods to enhance emergent technologies is the way forward. For example, path planning, a common transportation problem, can be extremely difficult when an exact solution is sought and automated vehicles will even cause more complex issues. Different approaches, more comparisons of optimization methods or conflict analyses are expected. Automation at scale and business analytics are two sectors, among others, expected to reap benefits sooner than later..
CASE STUDIES — … buy this booklet from Amazon …
CONCLUSIONS — Many artificial intelligence problems are Operations Research problems, dealing with the optimal allocation of resources or decision science. How to play the role of big data and artificial intelligence has become a topic of concern in military operations research. It is generally not harmful to add negative learning, because the globally best-performing algorithm variant makes use of negative learning. Several distributed reinforcement learning techniques involving the collective experience of artificial ants when approaching a transportation problem are analyzed. Transportation in the Age of Artificial Intelligence and Predictive Analytics is another topic with strong operations traction. A novel, scalable algorithm is capable of learning a structured, optimized diagnosis model for cyber-physical systems with comparable accuracy to standard approaches but higher interpretability. he ultra-edge IoT nodes are resource-constrained, so they need lightweight AI models for decision making and data delivery. The most widely used solution algorithms for facility layout planning are metaheuristic: genetic algorithms, simulated annealing, particle swarm, tabu search, ant colony and variable neighborhood searches. At industrial level, a set of five AI technology systems that solve business problems is made of: robotics and autonomous vehicles, computer vision, language, virtual agents, and machine learning. Research on deep learning for business analytics from an operational point of view is focused on justification, added value and guidelines.
TEN FREE REFERENCES FROM THE INTERNET — … buy this booklet from Amazon …
booklet updated on 19 Jun 2021, now on sale as version 1.2