Centre for the Study of Complexity

"Science is exploration – exploration for the sake of exploration, and for nothing else. We must go where our curiosity leads us, we must go where we want to go. And eventually, it is sure to lead us to the beautiful, the important, and the useful." - Robert Aumann

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About

The Centre for the Study of Complexity is a multidisciplinary research unit of Babes-Bolyai University, Cluj-Napoca aiming to explore the frontiers of complexity and build a network of powerful emerging ideas.

Complex real-world problems require novel approaches able to tackle subtle aspects of emergence, auto-organization and evolution. The fundamental principles in complex physical, computational, biological, economical and social systems are intensively studied by bringing together expertise from various fields.

We are a research team working on new natural computing models in the study of complexity.

Motivation

Mastering complexity emerges as an ubiquitous problem today and a key element of the modern society. Quoting C. Brancusi one can say that simplicity is solved complexity. Real world problems are highly complex in the sense that they involve many complex (usually unpredictable) interactions, dynamically changing environments, huge dimensionality, requiring optimization among many contradictory criteria. In order to cope with complexity, a shift in paradigm is imperative. Simply increasing the computing power is not a solution any more. The shifting paradigm should address two strategic concerns:

(i) the approach to large scale distributed computing and

(ii) the resulting complexity.

Nature inspired techniques in problem solving benefit from the tremendous optimizing power developed by nature. To give a single example, the circulatory system as evolved by nature has been mathematically proven to be optimal. Models of computation inspired by nature have the unique feature of evolving highly complex behaviour from simple interactions of many elements.

The main objective of this center is to explore more subtle facets of complexity than those commonly investigated by standard approaches. In order to achieve this objective, various natural computing paradigms will be investigated and engaged as a general problem solving framework in conjunction with game theory concepts as alternate solutions.

 

Researh interests

  1. Novel search and optimization computational intelligence techniques
    • Large scale optimization;
    • Multi-objective/Multi-criteria optimization;
    • Combinatorial optimization – packing and scheduling problems;
    • Optimization in uncertain and dynamic environments
    • Real world applications;
  2. Data mining
    • Cluster analysis
    • Decision support systems – prediction and simulations
  3. Game theory (GT) and applications
    • Algorithmic game theory; equilibria concepts
    • Evolutionary equilibrium detection;
    • Many-player games;
    • Games on networks;
    • Multi-criteria games;
    • Applications;
    • GT based Decision makings;
    • Dynamic games and applications;
  4. Study of complexity
    • Structure detection in complex networks;
    • Information flow in complex networks;
    • Game theoretical tools for complexity analysis;
    • GT analysis of emergent phenomena and complex systems;
    • Brain networks analysis;
    • Emergence of cooperation intra/inter groups;
    • Modeling social interactions;
  5. Computational and behavioral Economics;
Meet us!

People

D. Dumitrescu

artificial intelligence, natural computing

1949-2016

Rodica Ioana Lung

game theory, evolutionary optimization, complex networks

Gaskó Noémi

game theory, evolutionary algorithms

Mihai Suciu

evolutionary optimization, game theory, web services composition

Tudor Dan Mihoc

game theory, evolutionary computation

Crina Groșan

multiobjective optimization, systems biology

David Iclănzan

artificial intelligence, optimization techniques

Simon Károly

neural networks, evolutionary optimization

Csató Lehel

machine learning, artificial intelligence

Camelia Chira

evolutionary computation, complex networks

Bartha Attila

evolutionary games, optimization

Nagy Réka

evolutionary optimization, game theory

Bodó Zalán

machine learning, formal languages

Florin Duma

finance, financial management, capital markets, entrepreneurship

Szenkovits Annamária

model-based testing, safety-critical systems

Drd. Florentin Bota

artificial intelligence, multi-agent simulation

Drd. Emil Bucur

Publications

Publications (selection)

Lung, R. I., Gaskó, N., & Suciu, M. A. (2020). Pareto-based evolutionary multiobjective approaches and the generalized Nash equilibrium problem. Journal of Heuristics, 1-24.

Lung, Rodica Ioana, and Mihai-Alexandru Suciu. Equilibrium in Classification: A New Game Theoretic Approach to Supervised Learning. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, 137–138. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377929.3390001.

Suciu, Mihai-Alexandru, and Rodica Ioana Lung. Nash Equilibrium as a Solution in Supervised Classification. In Parallel Problem Solving from Nature – PPSN XVI, edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, and Heike Trautmann, 539–51. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2020. https://doi.org/10.1007/978-3-030-58112-1_37.

N. Kis and N. Gaskó, Community detection in multiplex networks with a genetic algorithm using a semi-aggregate method, 2020 IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI), Herlany, Slovakia, 2020, pp. 245-250, doi: 10.1109/SAMI48414.2020.9108736.

Képes, T., Gaskó, N., Lung, R. I., & Suciu, M. A. (2019, September). Influence Maximization and Extremal Optimization. In International Conference on Hybrid Artificial Intelligence Systems (pp. 416-427). Springer, Cham.

Gaskó, N., Suciu, M. A., Képes, T., & Lung, R. I. (2019, September). Shapley Value and Extremal Optimization for the Network Influence Maximization Problem. In 2019 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) (pp. 182-189). IEEE.

Bas, E., Egrioglu, E., Yolcu, U., & Grosan, C. (2019). Type 1 fuzzy function approach based on ridge regression for forecasting. Granular Computing, 4(4), 629-637.

Lung, R. I., Gaskó, N., & Suciu, M. A. (2018). A hypergraph model for representing scientific output. Scientometrics, 1-19.

Szenkovits, A., Meszlényi, R., Buza, K., Gaskó, N., Lung, R. I., & Suciu, M. (2018). Feature Selection with a Genetic Algorithm for Classification of Brain Imaging Data. In Advances in Feature Selection for Data and Pattern Recognition (pp. 185-202). Springer, Cham.

Lung, R. I. (2018). Adaptive artificial chemistry for Nash equilibria approximation. International Journal of Computational Intelligence Studies, 7(2), 93-102.

Nagy, R., Suciu, M., & Dumitrescu, D. (2018). Cooperation in Multicriteria Repeated Games. In EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI (pp. 107-117). Springer, Cham.


Gaskó, N., Suciu, M. A., & Lung, R. I. (2017, September). Computation of Berge-Zhukovskii Equilibrium in Discrete Time Dynamic Games. In International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding (pp. 24-33). Springer, Cham.

Lung, R. I., Suciu, M. A., & Gaskó, N. (2017, September). About Nash Equilibrium, Modularity Optimization, and Network Community Structure Detection. In International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding (pp. 209-218). Springer, Cham.

Gaskó, N., Bota, F., Suciu, M., & Lung, R. I. (2017, July). Community structure detection in multipartite networks: a new fitness measure. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 259-265). ACM.

Gaskó, N., Suciu, M., & Lung, R. I. (2017, June). Dynamic Generalized Berge-Zhukovskii Equilibrium. In 23rd International Conference on Soft Computing (pp. 311-319). Springer, Cham.

Lung, R. I., Suciu, M. A., & Gaskó, N. (2017, June). Exploring the Map Equation: Community Structure Detection in Unweighted, Undirected Networks. In 23rd International Conference on Soft Computing (pp. 245-253). Springer, Cham.

Lung, R. I., Suciu, M., & Gaskó, N. (2017). Noisy extremal optimization. Soft Computing, 21(5), 1253-1270.

Mihai-Alexandru, Suciu, Gaskó Noémi, and Lung Rodica Ioana. Approximation of Nash equilibria and the network community structure detection problem. PloS one 12, no. 5 (2017): e0174963.

Cremene, L., Gaskó, N., Cremene, M., Suciu, M., Vlaicu, A., & Dumitrescu, D. (2017). Scarce-resource capacity sharing in cognitive radio environments: a new game theoretical model. Telecommunication Systems, 66(2), 331-342.


Mihoc, T. D., Lung, R. I., Gaskó, N., & Suciu, M. (2016, July). Approximation of (k, t)-robust Equilibria. In Proceedings of the 2016 on Genetic and Evolutionary Computation Conference (pp. 805-811). ACM.

Suciu, M., Lung, R. I., & Gaskó, N. (2016, July). Game theory, Extremal optimization, and Community Structure Detection in Complex Networks. In Proceedings of the 2016 on Genetic and Evolutionary Computation Conference (pp. 405-412). ACM.

Szenkovits, A., Gaskó, N., & Jahier, E. (2016, March). Environment-Model Based Testing with Differential Evolution in an Industrial Setting. In European Conference on the Applications of Evolutionary Computation (pp. 819-830). Springer International Publishing.

Gaskó, N., Lung, R. I., & Suciu, M. A. (2016). A new network model for the study of scientific collaborations: Romanian computer science and mathematics co-authorship networks. Scientometrics, 1-20.

Cremene, M., Suciu, M., Pallez, D., & Dumitrescu, D. (2016). Comparative analysis of multi-objective evolutionary algorithms for QoS-aware web service composition. Applied Soft Computing, 39, 124-139.

Lung, R. I., Suciu, M., Meszlényi, R., Buza, K., & Gaskó, N. (2016, September). Community Structure Detection for the Functional Connectivity Networks of the Brain. In International Conference on Parallel Problem Solving from Nature (pp. 633-643). Springer International Publishing.

Lung, R. I. (2016). Direct Evolutionary Search for Nash Equilibria Detection. International Journal of Computers, Communications & Control, 11(4).


Lung, R. I., Suciu, M., Gaskó, N., & Dumitrescu, D. (2015). Characterization and Detection of ϵ-Berge-Zhukovskii Equilibria. PloS one, 10(7), e0131983.

Suciu, M., Lung, R. I., & Gaskó, N. (2015, April). Mixing Network Extremal Optimization for Community Structure Detection. In European Conference on Evolutionary Computation in Combinatorial Optimization (pp. 126-137). Springer International Publishing.

Lung, R. I., Suciu, M., & Gaskó, N. (2015). Noisy extremal optimization. Soft Computing, 1-18.


Lung, R. I., Chira, C., & Andreica, A. (2014). Game theory and extremal optimization for community detection in complex dynamic networks. PloS one, 9(2), e86891.

Gaskó, N., Lung, R. I., Suciu, M., & Dumitrescu, D. (2014). FIRST PRICE AND SECOND PRICE AUCTION GAMES. EQUILIBRIA DETECTION. Studia Universitatis Babes-Bolyai, Informatica, 59.

Gaskó, N., Suciu, M., Lung, R. I., & Dumitrescu, D. (2014). Berge-Zhukovskii Optimal Nash Equilibria. In EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (pp. 43-51). Springer International Publishing.

Suciu, M., Gaskó, N., Lung, R. I., & Dumitrescu, D. (2014). Nash equilibria detection for discrete-time generalized cournot dynamic oligopolies. In Nature Inspired Cooperative Strategies for Optimization (NICSO 2013) (pp. 343-354). Springer International Publishing.


Suciu, M., Lung, R. I., Gaskó, N., & Dumitrescu, D. (2013, June). Differential evolution for discrete-time large dynamic games. In 2013 IEEE Congress on Evolutionary Computation (pp. 2108-2113). IEEE.

Gaskó, N., Suciu, M., Lung, R.I., Mihoc, T.D., & Dumitrescu, D. (2013). PLAYERS WITH UNEXPECTED BEHAVIOR: t-IMMUNE STRATEGIES. AN EVOLUTIONARY APPROACH. Studia Universitatis Babes-Bolyai, Informatica, 58(2).

Iclănzan, D., Gaskó, N., Nagy, R., & Dumitrescu, D. (2013, January). Multiobjective Evolution of Mixed Nash Equilibria. In International Conference on Learning and Intelligent Optimization (pp. 304-314). Springer Berlin Heidelberg.

Suciu, M., Gasko, N., & Dumitrescu, D. (2013). Evolutionary Dynamic for Inter-Group Cooperation. ROMANIAN JOURNAL OF INFORMATION SCIENCE AND TECHNOLOGY, 16(2-3), 203-216.

Cremene, L. C., Gaskó, N., Cremene, M., & Dumitrescu, D. (2013). A Game Theoretical Perspective on Small-Cell Open Capacity Sharing in Cognitive Radio Environments. In Internet of Things, Smart Spaces, and Next Generation Networking (pp. 247-259). Springer Berlin Heidelberg.


Nagy, R., Gaskó, N., Lung, R. I., & Dumitrescu, D. (2012, September). Between Selfishness and Altruism: Fuzzy Nash–Berge-Zhukovskii Equilibrium. In International Conference on Parallel Problem Solving from Nature (pp. 500-509). Springer Berlin Heidelberg.

Cremene, L. C., Dumitrescu, D., Nagy, R., & Gasko, N. (2012, July). Cognitive radio simultaneous spectrum access/one-shot game modelling. In Communication Systems, Networks & Digital Signal Processing (CSNDSP), 2012 8th International Symposium on (pp. 1-6). IEEE.

Iclanzan, D., Gaskó, N., & Dumitrescu, D. (2012, July). Evolving mixed nash equilibria for bimatrix games. In Proceedings of the 14th annual conference companion on Genetic and evolutionary computation (pp. 655-656). ACM.

Gasko, N., Suciu, M., Lung, R.I., & Dumitrescu, D. (2012). Pareto-optimal Nash equilibrium detection using an evolutionary approach. Acta Univ. Sapientiae, 4(2), 237-246.

Gaskó, N., Lung, R. I., & Dumitrescu, D. (2012). Strong Berge and Strong Berge Pareto Equilibrium Detection Using an Evolutionary Approach. In Applied Computational Intelligence in Engineering and Information Technology (pp. 51-58). Springer Berlin Heidelberg.


Mihoc, T. D., Lung, R. I., Gaskó, N., & Dumitrescu, D. (2011). NONDOMINATION IN LARGE GAMES: BERGE-ZHUKOVSKII EQUILIBRIUM. Studia Universitatis Babes-Bolyai, Informatica, 56(2).

Dumitrescu, D., Lung, R. I., & Gaskó, N. (2011). An Evolutionary Approach of detecting some refinements of the Nash equilibrium. Studia Universitatis Babes-Bolyai, Series Informatica, 113-118.

Dumitrescu, D., Lung, R. I., & Gaskó, N. (2011, May). Detecting strong Berge Pareto equilibrium in a non-cooperative game using an evolutionary approach. In Applied Computational Intelligence and Informatics (SACI), 2011 6th IEEE International Symposium on (pp. 101-104). IEEE.

Gaskó, N., Dumitrescu, D., & Lung, R. I. (2011). MODIFIED STRONG AND COALITION PROOF NASH EQUILIBRIA. AN EVOLUTIONARY APPROACH. Studia Universitatis Babes-Bolyai, Informatica, 56(1).

Gaskó, N., Dumitrescu, D., & Lung, R. I. (2011, January). Detecting different joint equilibria with an evolutionary approach. In 2011 IEEE 9th International Symposium on Applied Machine Intelligence and Informatics (SAMI).

Gaskó, N., Dumitrescu, D., & Lung, R. I. (2011). Evolutionary detection of Berge and Nash equilibria. In Nature Inspired Cooperative Strategies for Optimization (NICSO 2011) (pp. 149-158) Springer Berlin Heidelberg.

Rodica I. Lung, D. Dumitrescu, A New Evolutionary Approach to Minimax Problems, IEEE Congress on Evolutionary Computation, CEC 2011.

Rodica I. Lung, T. D. Mihoc, D. Dumitrescu, Nash Extremal Optimization and Large Cournot Games, IEEE Congress on Evolutionary Computation, CEC 2011.

Reka Nagy, D. Dumitrescu, Rodica I. Lung, Fuzzy Equilibria for Games Involving n > 2 Players, IEEE Congress on Evolutionary Computation, CEC 2011.

Rodica Ioana Lung, Tudor Dan Mihoc, D. Dumitrescu, Nash Extremal Optimization and Large Cournot Games, Nature inspired Cooperative Strategies for Optimization (NICSO 2011), pp. 195-203, 2011.

Andrei Sirghi, D. Dumitrescu, Cooperation and Self-organized Criticality for Studying Economic Crises, Nature inspired Cooperative Strategies for Optimization (NICSO 2011), pp.225-237, 2011.

David Iclanzan, D. Dumitrescu, Laszlo Szilagyi, Sandor Szilagyi, “A Multi-Parent Search Operator for Bayesian Network Building”, Coping with Complexity, pp. 168-173, 2011.

Réka Nagy, D. Dumitrescu, Rodica Ioana Lung, “Lorenz Equilibrium: Concept and Evolutionary Detection”, 13th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2011), pp. 408-413, 2012.

Camelia Chira, Dragos Horvath and D. Dumitrescu, Hill-Climbing Search and Diversification within an Evolutionary Approach to Protein Structure Prediction, BioData Mining 2011, 4:23 (30 July 2011)

A. Gog, C. Chira, D. Dumitrescu, Evolutionary Community Structure Detection, Annals of West University of Timisoara, Series of Mathematics and Informatics, vol. XLIX, no.1, 2011, p. 39-48


Dumitrescu, D., Lung, R. I., & Gaskó, N. (2010, November). An evolutionary approach for detecting Aumann equilibrium in Congestion games. In 2010 11th International Symposium on Computational Intelligence and Informatics (CINTI).

Dumitrescu, D., Lung, R. I., Gasko, N., & Nagy, R. (2010, September). Job Scheduling and Bin Packing from a Game Theoretical Perspective: An Evolutionary Approach. In Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2010 12th International Symposium on (pp. 209-214). IEEE.

Dumitrescu, D., Lung, R. I., Gaskó, N., & Dan, T. M. (2010, July). Evolutionary detection of Aumann equilibrium. In Proceedings of the 12th annual conference on Genetic and evolutionary computation (pp. 827-828). ACM.

C. Chira, D. Dumitrescu, C.-M. Pintea, Learning Sensitive Stigmergic Agents for Solving Complex Problems, Computing and Informatics, Vol. 29, 2010, 1001-1020.

C. Chira, D. Dumitrescu, Evolutionary Models for Protein Folding Simulations in the Simplified HP Model, International Journal of Computers, Communications and Control, Vol. 5, Issue 5, 2010.

C-M.Pintea C.Chira, D.Dumitrescu, P.C. Pop: Sensitive Ants in Solving the Generalized Vehicle Routing Problem, International Journal of Computers,Communications & Control (IJCCC), Vol. 5, Issue 5, 2010.

C. Chira, D. Horvath, D. Dumitrescu, An Evolutionary Model based on Hill-Climbing Search Operators for Protein Structure Prediction, European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoStar 2010, EvoBIO 2010, LNCS 6023, pp. 38–49, 2010.

Dumitrescu, D., Lung, R., Nagy, R., Zaharie, D., and Bartha, A. 2010. Exploring evolutionary detected fuzzy equilibria: a link between normative theory and real life. In Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation (Portland, Oregon, USA, July 07 - 11, 2010). GECCO '10. ACM, New York, NY, 539-540. DOI= http://doi.acm.org/10.1145/1830483.1830582

Dumitru Dumitrescu, Rodica Ioana Lung, Tudor Dan Mihoc and Reka Nagy, Fuzzy Nash-Pareto Equilibrium: Concepts and Evolutionary Detection, APPLICATIONS OF EVOLUTIONARY COMPUTATION Lecture Notes in Computer Science, 2010, Volume 6024/2010, 71-79, DOI: 10.1007/978-3-642-12239-2_8

T. D. Mihoc, R. I. Lung, D. Dumitrescu, Notes on a Fitness Solution for Nash Equilibria in Large Games , CINTI 2010, pag.53-56, IEEE catalog number: CFP -1024 M-PRT; ISBN 978-1-4244-9278-7.

Lung, R. I., Mihoc, T. D., Dumitrescu, D., Nash equilibria detection for multi-player games, Evolutionary Computation (CEC), 2010a IEEE Congress on, 2010, 1-5.

Lung, R. I., Mihoc, T.D., Dumitrescu, D., Notes on Nash Equilibria Detection for Large Cournot Games, 12th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Timisoara, IEEE Press, 2010.

Dumitrescu D., Lung R.I., Mihoc T.-D., Meta-Rationality in Normal Form Games, International Journal of Computers Communications & Control, ISSN 1841-9836, 5(5): 693-700, 2010.

Dumitrescu, D., Lung, Rodica, and Mihoc, Tudor, Evolutionary Approaches to Joint Nash – Pareto Equilibria, Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), volume 284, Springer Berlin / Heidelberg, 233–243, Eds: González, Juan, Pelta, David, Cruz, Carlos, Terrazas, Germán, and Krasnogor, Natalio, 2010b, 10.1007/978-3-642-12538-6_20.

M. Sarasan, T. D. Mihoc R. I. Lung, D. Dumitrescu, Global Search and Local Ascent for Large Cournot Games, Studia Universitatis Babes Bolyai seria Informatica, 2010.

D. Dumitrescu, Andrei Sirghi, A Dynamical Game Model for Sustainable Development, Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), volume 284, Springer Berlin / Heidelberg, 151-162, 2010.

Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu, Multimodal Optimization by means of a Topological Species Conservation Algorithm, IEEE Transactions on Evolutionary Computation (5 Year Impact Factor: 7.621), IEEE Intelligence Computational Society, ISSN 1089-778X, 2010.

D. Dumitrescu, Rodica Ioana Lung, Réka Nagy, Daniela Zaharie, Attila Bartha, Doina Logofătu, Evolutionary Detection of New Classes of Equilibria. Application in Behavioral Games, 11th International Conference on Parallel Problem Solving From Nature (PPSN 2010), Lecture Notes in Computer Science, 2011, Volume 6239/2011, P. 432-441.


D. Dumitrescu, R. I. Lung, T. D. Mihoc, Evolutionary Equilibria Detection in Non-cooperative Games, Applications of Evolutionary Computing, EvoWorkshops 2009, Tubingen, Germany, April 15-17, 2009.

D. Dumitrescu, R. I. Lung, T. D. Mihoc, Evolutionary Equilibria Detection in Non-cooperative Games, Book Series: Lecture Notes in Computer Science, Publisher Springer Berlin / Heidelberg, Volume 5484 / 2009, Book: Applications of Evolutionary Computing, ISBN 978-3-642-01128-3, 2009, p. 253-262.

D. Dumitrescu, R. I. Lung, T. D. Mihoc, Generative Relations for Evolutionary Equilibria Detection, GECCO ’09, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, p. 1507-1512, New York, NY, USA, 8-12 July 2009. ACM. ISBN 978-1-60558-325-9, Index ISI.

D. Dumitrescu, R. I. Lung, T. D. Mihoc, Equilibria Detection In Electricity Market Games, Proceedings of the International Conference on Knowledge Engineering, Principles and Techniques, KEPT2009, Cluj-Napoca (Romania), July 2–4, 2009, pp. 111–114.

D. Dumitrescu, R. I. Lung, T. D. Mihoc, Approximating and Combining Equilibria in Non cooperative Games, Proceedings of the 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Timisoara, Romania, 2009.

R.I. Lung, D. Dumitrescu, Evolutionary swarm cooperative optimization in dynamic environments, Journal of Natural Computing, 10.1007/s11047-009-9129-9, 2009.

R.I. Lung, D. Dumitrescu, Evolutionary Multimodal Optimization for Nash Equilibria Detection, III International Workshop on Nature Inspired Cooperative Strategies for Optimization, NICSO, Springer Studies in Computational Intelligence, 2009.

D. Iclanzan, D. Dumitrescu, B. Hirsbrunner, Correlation guided model building, GECCO ’09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation, p. 421–428, New York, NY, USA, 8-12 July 2009. ACM. ISBN 978-1-60558-325-9.

László Szilágyi, David Iclanzan, Sándor M. Szilágyi, D. Dumitrescu, Béat Hirsbrunner, A generalized c-means clustering model using optimized via evolutionary computation, In IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’09, Jeju Island, Korea), p. 451–455, 2009.

C. Chira, C.-M. Pintea, D. Dumitrescu, Sensitive Stigmergic Agent Systems - A Hybrid Approach to Combinatorial Optimization, In Innovations in Hybrid Intelligent Systems, Advances in Soft Computing, Springer, vol 44, 33- 39, 2008.

P.C.Pop, C-M.Pintea, D.Dumitrescu, An Ant Colony algorithm for solving the dynamic generalized Vehicle Routing Problem, An. St. Univ. Ovidius Constanta, 2009 (ISSN: 1224-1784).

C. Chira, A. Gog, D. Dumitrescu, Asynchronous Collaborative Search using Adaptive Coevolving Subpopulations, ECOMASS Workshop, Genetic and Evolutionary Computation Conference GECCO’09, July 8-12, 2009, Montreal, Canada, F. Rothlauf (Ed), GECCO Companion, ACM, 2575-2582, 2009.

C. Chira, C.-M. Pintea, G. C. Crisan, D. Dumitrescu, Solving the Linear Ordering Problem using Ant Models, Genetic and Evolutionary Computation Conference, July 8-12, 2009, Montreal, Canada, F. Rothlauf (Ed), ACM, 1803-1804, 2009.

David Iclanzan, Béat Hirsbrunner, Michèle Courant, D. Dumitrescu, Cooperation in the context of sustainable search. In IEEE Congress on Evolutionary Computation (IEEE CEC 2009), 1904 – 1911, Trondheim, Norway, 18-21 May 2009.

C.-M. Pintea, G. C. Crisan, C. Chira, D. Dumitrescu, A Hybrid Ant-Based Approach to the Economic Triangulation Problem for Input-Output Tables, Real-world HAIS and Data Uncertainty, Proceedings of the 4th International Workshop on Hybrid Artificial Intelligence Systems (HAIS 2009), Salamanca, Spain, Lecture Notes in Computer Science, Vol. 5572, 376-383, Springer, 2009.

P.C.Pop, C.M.Pintea, I.Zelina, D.Dumitrescu, Solving the Generalized Vehicle Routing Problem with an ACS-based Algorithm, BICS 2008, American Institute of Physics (AIP)  Springer, vol.1117, 157-162, 2009.

C. Chira, C.-M. Pintea, D. Dumitrescu, Multi-Population Agent Search: Stigmergy and Heterogeneity, SYNASC 08, IEEE Computer Society, 526-531, 2009.

A. Gog, C. Chira, D. Dumitrescu, Distributed Asynchronous Collaborative Search, Studia Universitatis Babes-Bolyai, Informatica Series, Special Issue, 99 – 102, 2009.

Chira, C.-M. Pintea, D. Dumitrescu, A Step-Back Sensitive Ant Model for Solving Complex Problems, Studia Universitatis Babes-Bolyai, Informatica Series, Special Issue, 103-106, 2009.

R. Stoean, M. Preuss, C. Stoean, E. El-Darzi, D. Dumitrescu, An Evolutionary Approximation for the Coefficients of Decision Functions within a Support Vector Machine Learning Strategy Foundations on Computational Intelligence, Studies in Computational Intelligence, Springer, Aboul Ella Hassanien and Ajith Abraham (Eds.), Vol. 1, pp. 83-114, ISSN 1860-949X, 2009.

R. Stoean, M. Preuss, C. Stoean, E. El-Darzi, D. Dumitrescu, An Evolutionary Resemblant to Support Vector Machines for Classification and Regression, Journal of the Operational Research Society, Palgrave Macmillan, Vol. 60, Issue 8 (August 2009), Special Issue: Data Mining and Operational Research: Techniques and Applications, Guest Editors: Kweku-Muata Osei-Bryson and Vic J Rayward-Smith, pp. 1116-1122, ISSN 0160-5682, 2009, Index ISI.

C.M. Pintea, C. Chira, D. Dumitrescu, Results of Ant-Based Models for Solving the Linear Ordering Problem, Proceedings of the 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Timisoara, Romania, 2009, IEEE Computer Society Press.

C. Chira, C-M. Pintea, D. Dumitrescu, An Agent-Based Approach to Combinatorial Optimization, Int. J. of Computers, Communications & Control, ISSN 1841-9836, E-ISSN 1841-9844, Vol. III (2008), Suppl. Issue, pp. 212-217, Index ISI.

C-M. Pintea, C. Chira, D.Dumitrescu, Sensitive Ants: Inducing Diversity in the Colony Nature Inspired Cooperative Strategies for Optimization, Series "Studies in Computational Intelligence", Vol. 236 ( Krasnogor, N.; Melián-Batista, B.; Moreno-Pérez, J.A.; Moreno-Vega, J.M.; Pelta, D.; Eds.)  Springer-Verlag, 2009a (ISBN: 978-3-642-03210-3), Index ISI.

C. Chira, A. Gog, D. Zaharie, D. Dumitrescu, Complex Dynamics in a Collaborative Evolutionary Search Model Creative Mathematics and Informatics, vol. 17, nr. 3, 2009, Index BDI.

A.Gog, C. Chira. D. Dumitrescu, Asynchronous Evolutionary Search: Multi-Population Collaboration and Complex Dynamics, Proceedings of IEEE Congress on Evolutionary Computation (CEC 2009), Trondheim, Norway, 2009b, p. 240-246, Index ISI.

Alexandra-Roxana Tanase, D. Dumitrescu, Solving routing in telecomunication problems using sensitive ants, Acta Univ. Sapientiae, Informatica, 1,2 (2009) 259-266.

Lung R.I., Dumitrescu D., Computing Nash Equilibria by Means of Evolutionary Computation, International Journal of Computers Communications & Control, ISSN 1841-9836, Volume:3, Supplement: Suppl.S pp:364-368, 2008.

David Iclanzan, D. Dumitrescu, How can artificial neural networks help making the intractable search spaces tractable. In 2008 IEEE World Congress on Computational Intelligence (WCCI 2008), p. 4016–4023, Hong-Kong, 01-06 June 2008. ISBN 978-1-4244-1823-7.

David Iclanzan, D. Dumitrescu, Towards memoryless model building. In GECCO ’08: Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation, p. 2147–2152, Atlanta, GA, USA, 2008. ACM.

David Iclanzan, D. Dumitrescu, Large-scale optimization of non-separable building-block problems. In PPSN 2008: 10th International Conference on Parallel Problem Solving From Nature, p. 899–908, Dortmund, Germany, 13-17 September 2008.

David Iclanzan, D. Dumitrescu, Going for the big fish: Discovering and combining large neutral and massively multimodal building-blocks with model based macro-mutation. In GECCO ’08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, p. 423–430, Atlanta, GA, USA, 2008. ACM.

C. Chira, D. Dumitrescu, C-M. Pintea, Heterogeneous Sensitive Ant Model for Combinatorial Optimization, Genetic and Evolutionary Computation Conference GECCO’08, ACM, 163-164, July 12–16, 2008, Atlanta, Georgia, USA, 2008.

C. Chira, A. Gog, D. Dumitrescu, Exploring Population Geometry and Multi-Agent Systems: A New Approach to Developing Evolutionary Techniques, Genetic and Evolutionary Computation Conference GECCO’08, ACM, 1953-1959, July 12–16, 2008, Atlanta, Georgia, USA, 2008.

R. I. Lung, C. Chira, D. Dumitrescu, An Agent-Based Collaborative Evolutionary Model for Multimodal Optimization, Genetic and Evolutionary Computation Conference GECCO’08, ACM, 1969-1975, July 12–16, 2008, Atlanta, Georgia, USA, 2008.

László Szilágyi, David Iclanzan, Sándor M. Szilágyi, D. Dumitrescu, Gecim: A novel generalized approach to c-means clustering. In José Ruiz-Shulcloper, Walter G. Kropatsch, editors, CIARP, volume 5197 of Lecture Notes in Computer Science, p. 235–242. Springer, 2008.

Ruxandra Gorunescu, P.H. Millard, D. Dumitrescu, Evolutionary Placement Decisions of a Multidisciplinary Panel using Genetic Chromodynamics, Journal of Enterprise Information Management (INSPEC indexed), Vol. 21, No. 1, pp. 93-104, ISSN 1741-0398, 2008. 

Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu, EA-Powered Basin Number Estimation by Means of Preservation and Exploration, Parallel Problem Solving from Nature – PPSN X, Lecture Notes in Computer Science, Springer Berlin / Heidelberg, vol. 5199, pp 569-578, 2008, ISBN 978-3-540-87699-1.

Ruxandra Stoean, Catalin Stoean, D. Dumitrescu, Investigating Landscape Topology for Subpopulation Differentiation in Multimodal Evolutionary Algorithms. Study on Crowding Genetic Chromodynamics, IEEE Postproceedings, 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing - SYNASC 2008, IEEE Press, pp. 551-554, 2008.

Ruxandra Stoean, Catalin Stoean, D. Dumitrescu, Shifting from Radius-Centered Separation to Local Landscape Topology-Based Partition into Subpopulations within Crowding Genetic Chromodynamics, 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2008.

C. Chira, C.-M. Pintea, D. Dumitrescu, Stigmergy and Sensitivity in Heterogeneous Agent-Based Models, Workshop on Natural Computing and Applications, Proceedings of the 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2008), September 26-29,Timişoara, Romania, 2008, p.13-17.

C. Chira, A. Gog, D. Dumitrescu, Distribution, collaboration and coevolution in asynchronous search, Proceedings of the International Symposium on Distributed Computing and Artificial Intelligence (DCAI 2008), Salamanca, Spain, Advances in Soft Computing , Vol. 50, 2009, p.596-604.

A. Gog, C. Chira, D. Zaharie, D. Dumitrescu, Analysis of a Distributed Collaborative Evolutionary Algorithm, Workshop on Natural Computing and Applications, Proceedings of the 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2008), Timişoara, Romania, September 26-29, 2008, p. 25-32.

A. Gog, C. Chira, D. Dumitrescu, Hybrid Multi-Population Collaborative Asynchronous Search. Proceedings of the 3rd International Workshop on Hybrid Artificial Intelligence Systems (HAIS 2008), Burgos, Spain, September 24-26, Lecture Notes in Artificial Intelligence 5271, Springer, 2008, p. 148-155.

A. Gog, C. Chira, D. Dumitrescu, D. Zaharie, Analysis of Some Mating and Collaboration Strategies in Evolutionary Algorithms, Proc. of SYNASC 2008, IEEE Computer Science Publ.

C-M. Pintea, D. Dumitrescu, P.C. Pop, Combining Heuristics and Modifying Local Information to Guide Ant-based Search, Carpathian J.Math., 24(1), 94-103, 2008 (ISSN: 1584-2851).

C.-M. Pintea, P.C. Pop, C. Chira, D. Dumitrescu, A Hybrid Ant-Based System for Gate Assignment Problem. Proceedings of the 3rd International Workshop on Hybrid Artificial Intelligence Systems (HAIS 2008), Burgos, Spain, Lecture Notes in Artificial Intelligence 5271, Springer, 2008, p. 273-280.

C.-M. Pintea, C. Chira, D. Dumitrescu, P.C. Pop A Sensitive Metaheuristic for Solving a Large Optimization Problem, SOFSEM 2008: Theory and Practice of Computer Science, Lecture Notes in Computer Science 4910, Springer, V. Geffert, J. Karhumaki, A. Bertoni, B. Preneel, P. Navrat, M. Bielikova (Eds), p. 551-559, 2008.

C. Chira, D. Dumitrescu, C-M. Pintea, Sensitive Ant Model for Combinatorial Optimization, 14th International Conference in Soft Computing MENDEL 2008, June18-20, M. Radomil (Ed), Brno University of Technology, 2008.

C. Chira, C.-M. Pintea, D. Dumitrescu, Stigmergy and Sensitivity in Heterogeneous Agent-Based Models, Workshop on Natural Computing and Applications, Proceedings of the 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2008), September 26-29,Timişoara, Romania, 2008, p.13-17.

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