Nature-Inspired Computations Using an Evolving Multi-set of Agents

A multiset of agents can mimic the evolution of the nature-inspired computations, e.g., genetic, self-organized criticality and active walker (swarm and ant intelligence) models. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of the agents, so that the system evolve reaches an equilibrium, a chaotic or a self-organized emergent state. Examples of natural evolution , including wasp nest construction through a probabilistic shape-grammar are provided.

[1]  Yoseph Bar-Cohen,et al.  Biologically inspired intelligent robots , 2003, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[2]  S. N. Dorogovtsev,et al.  Evolution of networks , 2001, cond-mat/0106144.

[3]  Robert Shapiro,et al.  A simpler origin for life. , 2007, Scientific American.

[4]  Paulo S. C. Alencar,et al.  Software Engineering for Multi-Agent Systems II , 2004 .

[5]  Werner Ebeling,et al.  Self-Organization, Active Brownian Dynamics, and Biological Applications , 2002, cond-mat/0211606.

[6]  Salima Hassas,et al.  Self-Organisation: Paradigms and Applications , 2003, Engineering Self-Organising Systems.

[7]  Salima Hassas,et al.  Self-organisation: Paradigms and applications , 2003 .

[8]  Jeng-Shyang Pan,et al.  Parallel Ant Colony Systems , 2003, ISMIS.

[9]  Paul Bourgine,et al.  Autopoiesis and Cognition , 2004, Artificial Life.

[10]  Michael Wooldridge,et al.  Introduction to multiagent systems , 2001 .

[11]  Yang Jun,et al.  Multi-agent Development Toolkits: An Evaluation , 2004, IEA/AIE.

[12]  J. van Leeuwen,et al.  Ant Algorithms , 2002, Lecture Notes in Computer Science.

[13]  Andrew Ilachinski,et al.  Cellular automata , 1968 .

[14]  Dr. Zbigniew Michalewicz,et al.  How to Solve It: Modern Heuristics , 2004 .

[15]  Hiroshi Tanaka,et al.  Artificial Life Applications of a Class of P Systems: Abstract Rewriting Systems on Multisets , 2000, WMP.

[16]  Moonis Ali,et al.  Innovations in Applied Artificial Intelligence , 2005 .

[17]  Lakhmi C. Jain,et al.  Knowledge-Based Intelligent Information and Engineering Systems , 2004, Lecture Notes in Computer Science.

[18]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[19]  Nobuyuki Matsui,et al.  Neural Chaos Scheme of Perceptual Conflicts , 2003, KES.

[20]  Andrew Ilachinski,et al.  Cellular Automata: A Discrete Universe , 2001 .

[21]  F. Chung,et al.  Complex Graphs and Networks , 2006 .

[22]  Jürgen Branke,et al.  Multi-swarm Optimization in Dynamic Environments , 2004, EvoWorkshops.

[23]  Robert Grabowski,et al.  An army of small robots. , 2003, Scientific American.

[24]  Sean J. A. Edwards,et al.  Swarming on the Battlefield , 2006 .

[25]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[26]  Susan Stepney,et al.  Artificial Immune Systems and the Grand Challenge for Non-classical Computation , 2003, ICARIS.

[27]  Telecommunications Board,et al.  Catalyzing Inquiry at the Interface of Computing and Biology , 2006 .

[28]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[29]  Bradley J Stith,et al.  Use of animation in teaching cell biology. , 2004, Cell biology education.

[30]  J. Davies,et al.  Molecular Biology of the Cell , 1983, Bristol Medico-Chirurgical Journal.

[31]  Andrew J. Cowell,et al.  Evaluating Agent Architectures: Cougaar, Aglets and AAA , 2003, SELMAS.

[32]  Shusaku Tsumoto,et al.  Foundations of Intelligent Systems, 15th International Symposium, ISMIS 2005, Saratoga Springs, NY, USA, May 25-28, 2005, Proceedings , 2005, ISMIS.

[33]  E. Izhikevich,et al.  Weakly connected neural networks , 1997 .

[34]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[35]  E. V. Krishnamurthy,et al.  On the compactness of subsets of digital pictures , 1978 .

[36]  Y. Shoham.  Introduction to Multi-Agent Systems , 2002 .

[37]  A. Turing.  The chemical basis of morphogenesis , 1952, Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences.

[38]  David Harel,et al.  A Grand Challenge: Full Reactive Modeling of a Multi-cellular Animal , 2003, HSCC.

[39]  Stephen Wolfram,et al.  A New Kind of Science , 2003, Artificial Life.

[40]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[41]  E. V. Krishnamurthy,et al.  Probabilistic parallel programming based on multiset transformation , 1995, Future Gener. Comput. Syst..

[42]  Luca Cardelli,et al.  Abstract Machines of Systems Biology , 2005, Trans. Comp. Sys. Biology.

[43]  Guy Theraulaz,et al.  Self-Organization in Biological Systems , 2001, Princeton studies in complexity.

[44]  D R Westhead,et al.  Petri Net representations in systems biology. , 2003, Biochemical Society transactions.

[45]  John R. Koza,et al.  Genetic Programming II , 1992 .

[46]  John W. Keele,et al.  Software agents in molecular computational biology , 2005, Briefings Bioinform..

[47]  Stuart A. Kauffman,et al.  ORIGINS OF ORDER , 2019, Origins of Order.

[48]  George Sugihara,et al.  Fractals in science , 1995 .

[49]  Vikram Krishnamurthy,et al.  Multiset Rule-Based Programming Paradigm for Soft-Computing in Complex Systems , 2006, Handbook of Nature-Inspired and Innovative Computing.

[50]  E. Thompson.  Mind in Life , 2007 .

[51]  V.K. Murthy,et al.  Distributed agent paradigm for soft and hard computation , 2006, J. Netw. Comput. Appl..

[52]  Marco Dorigo,et al.  Proceedings of the Third International Workshop on Ant Algorithms , 2002 .

[53]  David Harel,et al.  Reactive animation: realistic modeling of complex dynamic systems , 2005, Computer.