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Search-Based Software Engineering for Self-Adaptive Systems: Survey, Disappointments, Suggestions and Opportunities [article]

Tao Chen, Miqing Li, Ke Li, Kalyanmoy Deb
2020 arXiv   pre-print
Search-Based Software Engineering (SBSE) is a promising paradigm that exploits the computational search to optimize different processes when engineering complex software systems.  ...  Self-adaptive system (SAS) is one category of such complex systems that permits to optimize different functional and non-functional objectives/criteria under changing environments (e.g., requirements and  ...  ACKNOWLEDGEMENT We thank the doctoral researchers from the IDEAS laboratory at Loughborough University for their assistance in collecting and analyzing the data in this work.  ... 
arXiv:2001.08236v2 fatcat:it5rq62bxfexje2hvycfkkf7dq

Parallel Local Search [chapter]

Philippe Codognet, Danny Munera, Daniel Diaz, Salvador Abreu
2018 Handbook of Parallel Constraint Reasoning  
In this chapter we explore and discuss ways which lead to parallelization in local search.  ...  Over the last couple of decades, significant advances have been made in terms of the formalization, applicability and performance of these methods.  ...  Furthermore, multiple A-Teams can be run in parallel and exchange information through a migration manager agent.  ... 
doi:10.1007/978-3-319-63516-3_10 fatcat:ah7ngeucercjvbbo6qr757boq4

Online Scheduling of a Residential Microgrid via Monte-Carlo Tree Search and a Learned Model [article]

Hang Shuai, Haibo He
2020 arXiv   pre-print
At each time step, the optimal decision is obtained by conducting Monte-Carlo tree search (MCTS) with a learned model and solving an optimal power flow sub-problem.  ...  In this way, this approach can sequentially make operational decisions online without relying on a forecast model.  ...  Using these methods, we can make day-ahead scheduling according to the forecast information of all the future system state and the statistic distribution information of the uncertainties in the system.  ... 
arXiv:2005.06161v3 fatcat:mn6hqsqp7vbtpjehe6yqsni4s4

Design of an Optimal ANFIS Traffic Signal Controller by Using Cuckoo Search for an Isolated Intersection

Sahar Araghi, Abbas Khosravi, Doug Creighton
2015 2015 IEEE International Conference on Systems, Man, and Cybernetics  
Applying type-2 fuzzy logic systems and the recently introduced cuckoo search optimization method led to the development of an efficient traffic signal timing controller, which is extended for a network  ...  In addition, different optimization methods such as genetic algorithm, simulated annealing, and cuckoo search are used to obtain optimal parameters of the aforementioned controllers.  ...  Firstly, the GA performs a stochastic search, rather than a deterministic search. This is an effective way in finding the optimum solution in most of complex systems.  ... 
doi:10.1109/smc.2015.363 dblp:conf/smc/AraghiKC15 fatcat:uwxsjl42hfh4ld4vc5z2czeeli

Uncertainty in Self-Adaptive Software Systems [chapter]

Naeem Esfahani, Sam Malek
2013 Lecture Notes in Computer Science  
In this paper, we characterize the sources of uncertainty in self-adaptive software system, and demonstrate its impact on the system's ability to satisfy its objectives.  ...  We discuss the state-of-the-art for dealing with uncertainty in this setting, and conclude with a set of challenges, which provide a road map for future research.  ...  This work is partially supported by grant CCF-0820060 and CCF-1217503 from the National Science Foundation and grant N11AP20025 from Defense Advanced Research Projects Agency.  ... 
doi:10.1007/978-3-642-35813-5_9 fatcat:nm33oxfe3ja2zp7fxf7i22gkt4

How do we Evaluate Self-adaptive Software Systems? [article]

Ilias Gerostathopoulos
2021 arXiv   pre-print
managed system, the presence of uncertainties that affect the system behavior and hence need to be taken into account in data analysis, and the potential of managed systems to be reused across experiments  ...  for Adaptive and Self-Managing Systems (SEAMS).  ...  Managed systems can be reused across experiments in selfadaptive systems; including them in replication packages would create a basis for sound long-term research. B.  ... 
arXiv:2103.11481v1 fatcat:a3ivd7r55jbmjh4sfqxjngtt4m

An Extensible and Modular Design and Implementation of Monte Carlo Tree Search for the JVM [article]

Larkin Liu, Jun Tao Luo
2021 arXiv   pre-print
Flexible implementations of Monte Carlo Tree Search (MCTS), combined with domain specific knowledge and hybridization with other search algorithms, can be powerful for finding the solutions to problems  ...  In addition, the implementation is reasonably performant and accurate for standard MDP's.  ...  Acknowledgements We would like to acknowledge the kind support of our reviewers, and Maven Central Repository for repository hosting of our code base. Appendix A.  ... 
arXiv:2108.10061v1 fatcat:phtyonwkrfhxjg4z524bmb6k3q

Policy search for motor primitives in robotics

Jens Kober, Jan Peters
2010 Machine Learning  
In this paper, we study parametrized policy search methods and apply these to benchmark problems of motor primitive learning in robotics.  ...  We show that the proposed method out-performs them on an empirical benchmark of learning dynamical system motor primitives both in simulation and on a real robot.  ...  Acknowledgements We thank the anonymous reviewers for their valuable suggestions that helped us to significantly extend and improve the discussions in Sect. 4.  ... 
doi:10.1007/s10994-010-5223-6 fatcat:kybxwudepba4vfkagomq56q65q

Planning and Learning Using Adaptive Entropy Tree Search [article]

Piotr Kozakowski, Mikołaj Pacek, Piotr Miłoś
2021 arXiv   pre-print
We present the Adaptive Entropy Tree Search (ANTS) algorithm, a planning method based on the Principle of Maximum Entropy.  ...  Moreover, we theoretically show that ANTS enjoys exponential convergence in the softmax bandit setting.  ...  Our experiments were managed using https://neptune.ai. We would like to thank the Neptune team for providing us access to the team version and technical support.  ... 
arXiv:2102.06808v2 fatcat:vxq2p4qnovao7pelzng2jtsexe

Review of Relief Demand Forecasting Problem in Emergency Logistic System

Jianan Zhao, Cejun Cao
2015 Journal of Service Science and Management  
Demand forecasting on relief is the premise and basis of material allocation scheme in emergency logistic system.  ...  And elaborate the application of case-based reasoning, information entropy theory, considering safety stock in the field of relief-demand forecasting in detail, to provide reference for relief distribution  ...  And this paper is financially supported by the projects including 2014 Jinan University scientific research creativeness project for outstanding graduate and 2014 Jinan University Challenge Cup student  ... 
doi:10.4236/jssm.2015.81011 fatcat:q27if5kppnfbncjo7t2a7dnuya

Learning a Mixture of Search Heuristics [chapter]

Susan L. Epstein, Smiljana Petrovic
2011 Autonomous Search  
This work was supported in part by the National Science Foundation under IIS-0328743, IIS-0739122, and IIS-0811437.  ...  Acknowledgements ACE is a joint project with Eugene Freuder and Richard Wallace of The Cork Constraint Computation Centre. Dr. Wallace made important contributions to the DWL algorithm.  ...  Machine Learning and Mixtures of Experts In the face of uncertainty, a prediction algorithm draws upon theory and knowledge to forecast a correct decision.  ... 
doi:10.1007/978-3-642-21434-9_5 fatcat:2zpi5lyxnvgdneko24gvwogfge

A Survey of Monte Carlo Tree Search Methods

Cameron B. Browne, Edward Powley, Daniel Whitehouse, Simon M. Lucas, Peter I. Cowling, Philipp Rohlfshagen, Stephen Tavener, Diego Perez, Spyridon Samothrakis, Simon Colton
2012 IEEE Transactions on Computational Intelligence and AI in Games  
Monte Carlo Tree Search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling.  ...  It has received considerable interest due to its spectacular success in the difficult problem of computer Go, but has also proved beneficial in a range of other domains.  ...  Dealing with Uncertainty and Hidden Information Games with hidden information and stochastic elements often have intractably wide game trees for standard tree search approaches.  ... 
doi:10.1109/tciaig.2012.2186810 fatcat:z2o6xdkkjvhf3k6hybw65o5r44

Inferring efficient operating rules in multireservoir water resource systems: A review

Hector Macian‐Sorribes, Manuel Pulido‐Velazquez
2019 WIREs Water  
Coordinated and efficient operation of water resource systems becomes essential to deal with growing demands and uncertain resources in water-stressed regions.  ...  This paper reviews the state of the art in developing operating rules for multireservoir water resource systems, focusing on efficient system operation.  ...  Manuel Pulido-Velazquez: Investigation; methodology; resources; supervision; writing-original draft; and writing-review and editing.  ... 
doi:10.1002/wat2.1400 fatcat:rluaptmqznd3pf33xxuslvpq34

An Asset-Based Development Approach for Availability and Safety Analysis on a Flood Alert System

Fumio Machida, Jianwen Xiang, Kumiko Tadano, Shigeru Hosono
2015 2015 IEEE International Conference on Dependable Systems and Networks Workshops  
Efficient analysis of system dependability is thus a key to increase the productivity and quality of system development project in service provider.  ...  values and empirical data are incorporated into project asset on the premise of reuse.  ...  Dependency information can be specified in the semi-formal language, and thus it is easily adapted to a new system configuration.  ... 
doi:10.1109/dsn-w.2015.12 dblp:conf/dsn/MachidaXTH15 fatcat:4qjwa2duebe7bgtj7slzrqgmwe

Model Independent Search For New Physics At The Tevatron [article]

Georgios Choudalakis
2008 arXiv   pre-print
The result of this search, first in 1 fb-1 and then in 2 fb-1, is null, namely no considerable evidence of new physics was found.  ...  The Standard Model prediction is implemented in all final states simultaneously, and an array of statistical probes is employed to search for significant discrepancies between data and prediction.  ...  are managed.  ... 
arXiv:0805.3954v1 fatcat:ieq5chos5bderb3ltosi3i2xn4
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