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A Survey of Learning Classifier Systems in Games
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| Pengarang | : | Listyawati, Andayani |
| Nama Majalah/Jurnal | : | IEEE Computational intelligence |
| Volume / Edisi | : | 12 (No. 1) |
| Halaman | : | 42-55 |
| Abstrak | : | Games are becoming increasingly indispensable, not only for fun but also to support tasks that are more serious, such as education, strategic planning, and understanding of complex phenomena. Computational intelligence-based methods are contributing significantly to this development. Learning Classifier Systems (LCS) is a pioneering computational intelligence approach that combines machine learning methods with evolutionary computation, to learn problem solutions in the form of interpretable rules. These systems offer several advantages for game applications, including a powerful and flexible agent architecture built on a knowledgebased symbolic modeling engine; modeling flexibility that allows integrating domain knowledge and different machine learning mechanisms under a single computational framework; an ability to adapt to diverse game requirements; and an ability to learn and generate creative agent behaviors in real-time dynamic environments. We present a comprehensive and dedicated survey of LCS in computer games. The survey highlights the versatility and advantages of these systems by reviewing their application in a variety of games. The survey is organized according to a general game classification and provides an opportunity to bring this important research direction into the public eye. We discuss the strengths and weaknesses of the existing approaches and provide insights into important future research directions. |
Modeling the Tracking Area Planning Problem Using an Evolutionary Multi-Objective Algorithm
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | IEEE Computational intelligence |
| Volume / Edisi | : | 12 (No. 1) |
| Halaman | : | 29-41 |
| Abstrak | : | When planning the Tracking Areas (TAs) for a Long Term Evolution (LTE) network, the main concern of mobile operators is to achieve the minimization of both location update cost and paging cost. This paper proposes a new green field TA planning model using multi-objective optimization with constraints, aiming at finding a better trade-off between the two conflicting objectives. This new model integrates the network geographical information, therefore making it more realistic. Considering the impact of constraints, we design an evolutionary multi-objective algorithm based on a population decomposition strategy for the proposed model. Information about infeasible solutions can be fully utilized by population decomposition and thus the algorithmic efficiency can be greatly improved. A new coding scheme inspired by the famous four-color theorem is specially designed for this multi-objective TA planning model. Computer simulations are conducted and the quality of the new model is confirmed by comparing the results of the multi-objective model with those of a single-objective model. The essential role of the population decomposition strategy has also been identified by comparing the proposed algorithm with the Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). |
SUATU TINJAUAN ATAS KEMISKINAN
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisa |
| Volume / Edisi | : | X-3, MARET (No. 3) |
| Halaman | : | 243-262 |
| Abstrak | : | Abstrak tidak tersedia. |
MASALAH PENINGKATAN EFEKTIVITAS ORGANISASI PEMBANGUNAN DESA
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisa |
| Volume / Edisi | : | X-3, MARET (No. 3) |
| Halaman | : | 234-242 |
| Abstrak | : | - |
Bridging the Gap Between Forensics and Biometric-Enabled Watchlists for e-Borders
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | IEEE Computational intelligence |
| Volume / Edisi | : | 12 (No. 1) |
| Halaman | : | 16-28 |
| Abstrak | : | A biometric-enabled watchlist (or a database of persons of interest) is commonly accepted by national and international security agencies. In particular, the facetrait has demonstrated promising performance in large-scale open-set tasks in forensics and law enforcement scenarios. However, their application in the security of mass-transit systems, such as e-borders, is very limited. We evaluate the risks of unwanted effects using Doddington’s metric and various databases. The key contribution of this paper is a novel technique for traveler risk categorization using a biometric-enabled watchlist and an evidence-accumulation paradigm, as well as its impact on e-border performance. |
PENGEMBANGAN KESEMPATAN KERJA NONPERTANIAN DI PEDESAAN INDONESIA
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisa |
| Volume / Edisi | : | X-3, MARET (No. 3) |
| Halaman | : | 220-233 |
| Abstrak | : | - |
CIS Publication Spotlight
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | IEEE Computational intelligence |
| Volume / Edisi | : | 12 (No. 1) |
| Halaman | : | 13-15 |
| Abstrak | : | - |
GAMBARAN UMUM TENTANG PEMBANGUNAN PEDESAAN DI INDONESIA
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisa |
| Volume / Edisi | : | X-3, MARET (No. 3) |
| Halaman | : | 205-219 |
| Abstrak | : | - |
Conference Report on 2016 IEEE World Congress on Computational Intelligence (IEEE WCCI 2016)
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | IEEE Computational intelligence |
| Volume / Edisi | : | 12 (No. 1) |
| Halaman | : | 9-12 |
| Abstrak | : | - |
IEEE CIS VP-Education Vision Statement
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | IEEE Computational intelligence |
| Volume / Edisi | : | 12 (No. 1) |
| Halaman | : | 6-8 |
| Abstrak | : | - |