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Number of results: 7
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Abstract

Games are among problems that can be reduced to optimization, for which one of the most universal and productive solving method is a heuristic approach. In this article we present results of benchmark tests on using 5 heuristic methods to solve a physical model of the darts game. Discussion of the scores and conclusions from the research have shown that application of heuristic methods can simulate artificial intelligence as a regular player with very good results.
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Authors and Affiliations

Kamil Książek
Dawid Połap
Marcin Woźniak
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Abstract

A Computational Intelligence (CI) approach is one of the main trending and potent data dealing out and processing instruments to unravel and resolve difficult and hard reliability crisis and it takes an important position in intelligent reliability analysis and management of data. Nevertheless, just few little broad reviews have recapitulated the current attempts of Computational Intelligence (CI) in reliability assessment in power systems. There are many methods in reliability assessment with the aim to prolong the life cycles of a system, to maximize profit and predict the life cycle of assets or systems within an organization especially in electric power distribution systems. Sustaining an uninterrupted electrical energy supply is a pointer of affluence and nationwide growth. The general background of reliability assessment in power system distribution using computational intelligence, some computational intelligence techniques, reliability engineering, literature reviews, theoretical or conceptual frameworks, methods of reliability assessment and conclusions was discussed. The anticipated and proposed technique has the aptitude to significantly reduce the needed period for reliability investigation in distribution networks because the distribution network needs an algorithm that can evaluate, assess, measure and update the reliability indices and system performance within a short time. It can also manage outages data on assets and on the entire system for quick and rapid decisions making as well as can prevent catastrophic failures. Those listed above would be taken care of if the proposed method is utilized. This overview or review may be deemed as valuable assistance for anybody doing research.
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Authors and Affiliations

Elijah Adebayo Olajuyin
1
ORCID: ORCID
Paul Kehinde Olulope
2
Emmanuel Taiwo Fasina
2

  1. Bamidele Olumilua University of Education, Science and Technology, Ikere Ekiti, Nigeria
  2. Ekiti State University, Ado Ekiti, Nigeria
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Abstract

The issue of line simplification is one of the fundamental problems of generalisation of geographical information, and the proper parameterisation of simplification algorithms is essential for the correctness and cartographic quality of the results. The authors of this study have attempted to apply computational intelligence methods in order to create a cartographic knowledge base that would allow for non-standard parameterisation of WEA (Weighted Effective Area) simplification algorithm. The aim of the conducted research was to obtain two independent methods of non-linear weighting of multi-dimensional regression function that determines the “importance” of specific points on the line and their comparison to each other. The first proposed approach consisted in the preparation of a set of cartographically correct examples constituting a basis for teaching a neural network, while the other one consisted in defining inference rules using fuzzy logic. The obtained results demonstrate that both methods have great potential, although the proposed solutions require detailed parameterisation taking into account the specificity of geometric variety of the source data.

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Authors and Affiliations

Robert Olszewski
Miłosz Gnat
Anna Fiedukowicz
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Abstract

Computational intelligence (CI) can adopt/optimize important principles in the workflow of 3D printing. This article aims to examine to what extent the current possibilities for using CI in the development of 3D printing and reverse engineering are being used, and where there are still reserves in this area. Methodology: A literature review is followed by own research on CI-based solutions. Results: Two ANNs solving the most common problems are presented. Conclusions: CI can effectively support 3D printing and reverse engineering especially during the transition to Industry 4.0. Wider implementation of CI solutions can accelerate and integrate the development of innovative technologies based on 3D scanning, 3D printing, and reverse engineering. Analyzing data, gathering experience, and transforming it into knowledge can be done faster and more efficiently, but requires a conscious application and proper targeting.
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Authors and Affiliations

Izabela Rojek
1
ORCID: ORCID
Dariusz Mikołajewski
1
ORCID: ORCID
Joanna Nowak
2
ORCID: ORCID
Zbigniew Szczepański
2
ORCID: ORCID
Marek Macko
2
ORCID: ORCID

  1. Institute of Computer Science, Kazimierz Wielki University, Bydgoszcz, Poland
  2. Faculty of Mechatronics, Kazimierz Wielki University, Bydgoszcz, Poland
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Abstract

The article presents research on the use of Monte-Carlo Tree Search (MCTS) methods to create an artificial player for the popular card game “The Lord of the Rings”. The game is characterized by complicated rules, multi-stage round construction, and a high level of randomness. The described study found that the best probability of a win is received for a strategy combining expert knowledge-based agents with MCTS agents at different decision stages. It is also beneficial to replace random playouts with playouts using expert knowledge. The results of the final experiments indicate that the relative effectiveness of the developed solution grows as the difficulty of the game increases.
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Bibliography

  1.  C. Browne, “A survey of monte carlo tree search methods”, IEEE Trans. Comput. Intell. AI Games 4., 1–43 (2012).
  2.  R. Bjarnason, A. Fern, and P. Tadepalli, “Lower bounding Klondike solitaire with Monte-Carlo planning”, Nineteenth International Conference on Automated Planning and Scheduling, 2009.
  3.  M. Świechowski, T. Tajmajer, and A. Janusz, “Improving hearthstone ai by combining mcts and supervised learning algo rithms”, 2018 IEEE Conference on Computational Intelligence and Games (CIG), 2018.
  4.  J. Mańdziuk, “MCTS/UCT in Solving Real-Life Problems”, Advances in Data Analysis with Computational Intelligence Methods, 277‒292, Springer, Cham, 2018.
  5.  S. Kajita, T. Kinjo, and T. Nishi, “Autonomous molecular design by Monte-Carlo tree search and rapid evaluations using molecular dynamics simulations”, Commun. Phys. 3(1), 1‒11 (2020).
  6.  S. Haeri and L. Trajković, “Virtual network embedding via Monte Carlo tree search”, IEEE Trans. Cybern. 48(2), 510‒521 (2017).
  7.  G. Best, O.M. Cliff, T. Patten, R.R. Mettu, and R. Fitch, “Decentralised Monte Carlo tree search for active perception”, Algorithmic Foundations of Robotics XII, 864‒879, Springer, Cham, 2020.
  8.  D.A. Dhar, P. Morawiecki, and S. Wójtowicz. “Finding differential paths in arx ciphers through nested monte-carlo search”, AEU Int. J. Electron. Commun 64(2), 147‒150 (2018).
  9.  K. Guzek and P. Napieralski, “Measurement of noise in the Monte Carlo point sampling method”, Bull. Pol. Acad. Sci. Tech. Sci. 59(1), 15‒19 (2011).
  10.  D. Tefelski, T. Piotrowski, A. Polański, J. Skubalski and V. Blideanu, “Monte-Carlo aided design of neutron shielding concretes”, Bull. Pol. Acad. Sci. Tech. Sci. 61(1), 161‒171 (2013).
  11.  C.D. Ward and P.I. Cowling, “Monte Carlo search applied to card selection in Magic: The Gathering”, IEEE Symposium on Computational Intelligence and Games, 2009.
  12.  P.I. Cowling, C.D. Ward, and E.J. Powley, “Ensemble determinization in monte carlo tree search for the imperfect information card game magic: The gathering”, IEEE Trans. Comput. Intell. AI Games 4(4), 241‒257 (2012).
  13.  S. Turkay, S. Adinolf, and D. Tirthali, “Collectible Card Games as Learning Tools”, Procedia – Soc. Behav. Sci. 46, 3701‒3705 (2012), doi: 10.1016/j.sbspro.2012.06.130.
  14.  K. Bochennek, B. Wittekindt, S.-Y. Zimmermann, and T. Klingebiel, “More than mere games: a review of card and board games for medical education”, Med. Teach. 29(9), 941‒948 (2007), doi: 10.1080/01421590701749813.
  15.  J.S.B. Choe and J. Kim, “Enhancing Monte Carlo Tree Search for Playing Hearthstone”, 2019 IEEE Conference on Games (CoG), London, United Kingdom, 2019, pp. 1‒7.
  16.  K. Godlewski and B. Sawicki, “MCTS Based Agents for Multistage Single-Player Card Game”, 21st International Conference on Computational Problems of Electrical Engineering (CPEE), 2020
  17.  “Magic: The Gathering”, [online] https://magic.wizards.com/en
  18.  E.J. Powley, P.I. Cowling, and D. Whitehouse. “Information capture and reuse strategies in Monte Carlo Tree Search, with applications to games of hidden information”, Artif. Intell. 217, 92‒116 (2014).
  19.  Fantasy Flight Publishing, “Hall of Beorn”, technical documentation, 2020 [Online] Available: http://hallofbeorn.com/LotR/Scenarios/ Passage-Through-Mirkwood
  20.  S. Zhang and M. Buro, “Improving hearthstone AI by learning high-level rollout policies and bucketing chance node events”, 2017 IEEE Conference on Computational Intelligence and Games (CIG), New York, USA, 2017, pp. 309‒316.
  21.  G.M.J-B. Chaslot, M.H.M. Winands, and H.J. van Den Herik, “Parallel monte-carlo tree search”, International Conference on Computers and Games, Springer, Berlin, Heidelberg, 2008.
  22.  A. Fern and P. Lewis, “Ensemble monte-carlo planning: An empirical study”, Twenty-First International Conference on Automated Planning and Scheduling, ICAPS 2011, Germany, 2011.
  23.  A. Santos, P. A. Santos, and F.S. Melo, “Monte Carlo tree search experiments in hearthstone,” 2017 IEEE Conference on Computational Intelligence and Games (CIG), New York, USA, 2017, pp. 272‒279.
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Authors and Affiliations

Konrad Godlewski
1
Bartosz Sawicki
1

  1. Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
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Abstract

This short paper presents the activity and achievements of Professor Zenon Waszczyszyn, active member of Polish Academy of Sciences and Polish Academy of Arts and Sciences, Professor of Cracow University of Technology and Rzeszów University of Technology, doctor honoris causa of Budapest University of Technology and Economics, creator of scientific schools in the field of stability of engineering structures and mechanics of shell structures as well as in the field of computational intelligence methods, in particular artificial neural networks.
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Authors and Affiliations

Jerzy Pamin
1

  1. Wydział Inżynierii Lądowej Politechniki Krakowskiej
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Abstract

One way to ensure the required technical characteristics of castings is the strict control of production parameters affecting the quality of

the finished products. If the production process is improperly configured, the resulting defects in castings lead to huge losses. Therefore,

from the point of view of economics, it is advisable to use the methods of computational intelligence in the field of quality assurance and

adjustment of parameters of future production. At the same time, the development of knowledge in the field of metallurgy, aimed to raise

the technical level and efficiency of the manufacture of foundry products, should be followed by the development of information systems

to support production processes in order to improve their effectiveness and compliance with the increasingly more stringent requirements

of ergonomics, occupational safety, environmental protection and quality. This article is a presentation of artificial intelligence methods

used in practical applications related to quality assurance. The problem of control of the production process involves the use of tools such

as the induction of decision trees, fuzzy logic, rough set theory, artificial neural networks or case-based reasoning.

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Authors and Affiliations

S. Kluska-Nawarecka
K. Regulski
G. Rojek
D. Wilk-Kołodziejczyk
K. Jaśkowiec
A. Smolarek-Grzyb

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