We describe an Artificial Intelligence (AI) program for mechanical engineering design. The program, called Dominic, characterizes design as best-first search through a space of possible designs. Dominic is a general a...
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Adaptation, for purposes of self-healing, self-protection, self-management, or self-regulation, is currently considered to be one of the most challenging pr- erties of distributed systems that operate in dynamic, unpr...
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ISBN:
(数字)9783642023774
ISBN:
(纸本)9783642023767
Adaptation, for purposes of self-healing, self-protection, self-management, or self-regulation, is currently considered to be one of the most challenging pr- erties of distributed systems that operate in dynamic, unpredictable, and - tentially hostile environments. engineering for adaptation is particularly c- plicated when the distributed system itself is composed of autonomous entities that, on one hand, may act collaboratively and with benevolence, and, on the other,maybehavesel?***,theseentities have to coordinate themselves in order to adapt appropriately to the prevailing environmental conditions, and furthermore, to deliberate upon their own and the system’s con?guration, and to be transparent to their users yet consistent with any human requirements. The question, therefore, of “how to organize the envisagedadaptationforsuchautonomousentitiesinasystematicway”becomes of paramount importance. The ?rst international workshop on “Organized Adaptation in Multi-Agent Systems” (OAMAS) was a one-day event held as part of the workshop p- gram arranged by the international conference on Autonomous Agents and Multi-Agent Systems (AAMAS). It was hosted in Estoril during May, 2008, and was attended by more than 30 researchers. OAMAS was the steady convergence of a number of lines of research which suggested that such a workshop would be timely and opportune. This includes the areas of autonomic computing, swarm intelligence, agent societies, self-organizing complex systems, and ‘emergence’ in general.
The book constitutes the proceedings of the 23rd International Conference on Artificial Neural Networks, ICANN 2013, held in Sofia, Bulgaria, in September 2013. The 78 papers included in the proceedings were carefully...
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ISBN:
(数字)9783642407284
ISBN:
(纸本)9783642407277
The book constitutes the proceedings of the 23rd International Conference on Artificial Neural Networks, ICANN 2013, held in Sofia, Bulgaria, in September 2013. The 78 papers included in the proceedings were carefully reviewed and selected from 128 submissions. The focus of the papers is on following topics: neurofinance graphical network models, brain machine interfaces, evolutionary neural networks, neurodynamics, complex systems, neuroinformatics, neuroengineering, hybrid systems, computational biology, neural hardware, bioinspired embedded systems, and collective intelligence.
The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 r...
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ISBN:
(数字)9783642208416
ISBN:
(纸本)9783642208409
The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knowledgeengineering, behavior sciences, visualization, and emerging areas such as social network analysis.
This book constitutes the thoroughly refereed post-workshop proceedings of the 7th International Workshop on Agents and Data Mining Interaction, ADMI 2011, held in Taipei, Taiwan, in May 2011 in conjunction with AAMAS...
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ISBN:
(数字)9783642276095
ISBN:
(纸本)9783642276088
This book constitutes the thoroughly refereed post-workshop proceedings of the 7th International Workshop on Agents and Data Mining Interaction, ADMI 2011, held in Taipei, Taiwan, in May 2011 in conjunction with AAMAS 2011, the 10th International Joint Conference on Autonomous Agents and Multiagent Systems.;The 11 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers are organized in topical sections on agents for data mining; data mining for agents; and agent mining applications.
This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning refers to modern data transformation techniques that convert data of different mo...
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ISBN:
(数字)9783030688172
ISBN:
(纸本)9783030688165;9783030688196
This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning refers to modern data transformation techniques that convert data of different modalities and complexity, including texts, graphs, and relations, into compact tabular representations, which effectively capture their semantic properties and relations. The monograph focuses on (i) propositionalization approaches, established in relational learning and inductive logic programming, and (ii) embedding approaches, which have gained popularity with recent advances in deep learning. The authors establish a unifying perspective on representation learning techniques developed in these various areas of modern data science, enabling the reader to understand the common underlying principles and to gain insight using selected examples and sample Python code. The monograph should be of interest to a wide audience, ranging from data scientists, machine learning researchers and students to developers, software engineers and industrial researchers interested in hands-on AI solutions.
The Web 3.0 and metaverse can empower intelligent application of Connected Autonomous Vehicles (CAVs). The adoption of edge computing can contribute to the low latency interaction between CAVs and the metaverse. Micro...
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The Web 3.0 and metaverse can empower intelligent application of Connected Autonomous Vehicles (CAVs). The adoption of edge computing can contribute to the low latency interaction between CAVs and the metaverse. Microservices are widely deployed on edge networks and the cloud nowadays. User's requests from CAVs are typically fulfilled through the composition of microservices, which may be hosted by contiguous edge nodes. Requests may differ on their required resources at runtime. Consequently, when requests are continuously injected into edge networks, the usage of heterogenous resources, including CPU, memory, and network bandwidth, may not be the same, or differ significantly, on certain edge nodes. This happens especially when burst requests are injected into the network to be satisfied concurrently. Therefore, the usage of heterogenous resources provided by edge nodes should be co-optimized through re-scheduling microservices. To address this challenge, this paper proposes a Web 3.0-enabled Microservice Re-Scheduling approach (called MRS), which is a migration-based mechanism integrating a placement strategy. Specifically, we formulate the microservice re-scheduling task as a multi-objective and multi-constraint optimization problem, which can be solved through a penalty signal-integrated framework and an improved pointer network. Extensive experiments are conducted on two real-world datasets. Evaluation results show that our MRS performs better than the counterparts with improvements of at least 7.7%, 2.4% and 2.2% in terms of network throughput, latency and energy consumption.
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