Frontiers of Algorithmics: International Joint Conference, IJTCS-FAW 2021, Beijing, China, August 16-19, 2021, Proceedings

The 15th International Workshop on Frontiers in Algorithmics,FAW 2021,was held in Beijing, China, in August 2021, with 5 full papers presented. The conference, held in hybrid mode due to the COVID-19 pandemic, covered various topics in Algorithmic Game Theory, Blockchain, Multi-agent Reinforcement Learning, Quantum Computation, Theory of Machine Learning, Machine Learning, Formal Method, Algorithm and Complexity, and EconCS.

Format: Paperback / softback
Length: 79 pages
Publication date: 03 March 2022
Publisher: Springer Nature Switzerland AG

The 15th International Workshop on Frontiers in Algorithmics (FAW 2021) was held in conjunction with the second International Joint Conference on Theoretical Computer Science (IJTCS 2021), known as IJTCS-FAW 2021, in Beijing, China, in August 2021. Due to the COVID-19 pandemic, the conference was held in a hybrid mode, allowing participants to attend both in-person and virtually.

This book serves as a compilation of the proceedings from the workshop, encompassing five full papers that were meticulously reviewed and selected from a total of nine submissions. The conference provided a dedicated forum for researchers to explore various areas of Algorithmic Game Theory, Blockchain, Multi-agent Reinforcement Learning, Quantum Computation, Theory of Machine Learning, Machine Learning, Formal Method, Algorithm and Complexity, and EconCS.

Algorithmic Game Theory:

Algorithmic Game Theory is a branch of computer science that focuses on designing and analyzing algorithms for solving games. It involves developing mathematical models and techniques to analyze the strategic interactions between agents in games, and designing algorithms that optimize the performance of agents in terms of winning or achieving other objectives.

Blockchain:

Blockchain is a distributed ledger technology that enables secure and transparent transactions between multiple parties. It is widely used in various applications, such as finance, supply chain management, and healthcare. Blockchain technology has the potential to revolutionize the way we conduct transactions and exchange information, as it provides a decentralized and trustless system that is resistant to fraud and hacking.

Multi-agent Reinforcement Learning:

Multi-agent Reinforcement Learning is a subfield of artificial intelligence that involves training agents to interact and cooperate with each other to achieve a common goal. It is particularly useful in scenarios where agents need to make complex decisions and coordinate their actions to achieve optimal outcomes.

Quantum Computation:

Quantum Computation is a new computing paradigm that uses quantum bits, or qubits, to perform computations. It has the potential to solve complex problems that are currently intractable for classical computers, such as simulating the behavior of molecules and solving optimization problems.

Theory of Machine Learning:

Theory of Machine Learning is a branch of computer science that focuses on developing mathematical models and algorithms for learning from data. It involves developing techniques for training machine learning models, evaluating their performance, and making predictions based on the data.

Machine Learning:

Machine Learning is a subfield of artificial intelligence that involves the use of algorithms to learn from data and make predictions. It has applications in various fields, such as image recognition, natural language processing, and fraud detection. Machine learning algorithms are trained on large datasets of data to learn patterns and make predictions based on those patterns.

Formal Method:

Formal Method is a branch of computer science that involves the use of formal logic and mathematical techniques to design and analyze algorithms. It involves developing formal models of algorithms and proving their correctness and efficiency. Formal methods are used in various areas, such as software engineering, cryptography, and optimization.

Algorithm and Complexity:

Algorithm and Complexity is a branch of computer science that focuses on analyzing the time and space complexity of algorithms. It involves developing techniques for analyzing the performance of algorithms and designing efficient algorithms that can solve complex problems in a reasonable amount of time.

EconCS:

EconCS is a subfield of computer science that focuses on the intersection of computer science and economics. It involves developing algorithms and models for analyzing economic data and making predictions about economic trends and behaviors. EconCS has applications in various fields, such as finance, marketing, and logistics.

In conclusion, the 15th International Workshop on Frontiers in Algorithmics (FAW 2021) was a successful event that brought together researchers from around the world to explore the latest advancements in Algorithmic Game Theory, Blockchain, Multi-agent Reinforcement Learning, Quantum Computation, Theory of Machine Learning, Machine Learning, Formal Method, Algorithm and Complexity, and EconCS. The conference provided a platform for researchers to share their research findings, exchange ideas, and collaborate on future research projects. The book that captures the proceedings of the workshop is a valuable resource for researchers and practitioners in these fields.

Weight: 180g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030970987
Edition number: 1st ed. 2022