Basic Approach to Emergent Programming: Feasibility Study for Engineering Adaptive Systems Using Self-organizing Instruction-Agents
We propose to investigate the concept of an Emergent Programming Environment enabling the development of complex adaptive systems. This is done as a means to tackle the problems of the growth in complexity of programming, increasing dynamisms in artificial systems and environments, and the lack of knowledge about difficult problems and their solutions. For this we use as a foundation the concept of emergence and a multi-agent system technology based on cooperative self-organizing mechanisms.
The general objective is then to develop a complete programming language in which each instruction is an autonomous agent trying to be in a cooperative state with the other agents of the system, as well as with the environment of the system. By endowing these instruction-agents with self-organizing mechanisms, we obtain a system able to continuously adapt to the task required by the programmer (i.e. to program and re-program itself depending on the needs). The work presented here aims at showing the feasibility of such a concept by specifying, and experimenting with, a core of instruction-agents needed for a sub-set of mathematical calculus.
KeywordsSearch Space Global Function Ambient Intelligence Autonomic Computing Emergent Phenomenon
Unable to display preview. Download preview PDF.
- 2.Ball, P.: The Self-Made Tapestry. Oxford Press (1999)Google Scholar
- 5.Capera, D., Georgé, J., Gleizes, M.-P., Glize, P.: Emergence of organisations, emergence of functions. In: AISB 2003 symposium on Adaptive Agents and Multi-Agent Systems (April 2003)Google Scholar
- 8.Georgé, J., Edmonds, B., Glize, P.: Self-organizing adaptive multi-agent systems work, ch.16, pp. 321–340. Kluwer Publishing, Dordrecht (2004)Google Scholar
- 9.Georgé, J.-P.: Résolution de problèmes par émergence - Étude d’un Environnement de Programmation Émergente. PhD thesis, Université Paul Sabatier, Toulouse, France (2004), http://www.irit.fr/SMAC/EPE.html
- 10.Georgé, J.P., Gleizes, M.P., Glize, P., Régis, C.: Real-time simulation for flood forecast: an adaptive multi-agent system staff. In: Kazakov, D., Kudenko, D., Alonso, E. (eds.) Proceedings of the AISB 2003 symposium on Adaptive Agents and Multi-Agent Systems(AAMAS 2003), April 7-11 2003, pp. 109–114. University of Wales, Aberystwyth (2003)Google Scholar
- 11.Gleizes, P.-P., Camps, V., Glize, P.: A theory of emergent computation based on cooperative self-oganization for adaptive artificial systems. In: Fourth European Congress of Systems Science, Valencia, Spain (1999)Google Scholar
- 12.Heylighen, F.: Evolution, selfishness and cooperation; selfish memes and the evolution of cooperation. Journal of Ideas 2(4), 70–84 (1992)Google Scholar
- 13.Heylighen, F.: The Science of Selforganization and Adaptivity,Encyclopedia of Life Support Systems. EOLSS Publishers Co. Ltd (2001)Google Scholar
- 14.Horn, P.: Autonomic computing - ibm’s perspective on the state of information technology (2001), http://www.ibm.com/research/autonomic
- 15.Huberman, B.: The performance of cooperative processes. MIT Press / North-Holland, Cambridge (1991)Google Scholar
- 16.Koza, J.R.: Evolution and co-evolution of computer programs to control independently-acting agents. In: From animals to animats: proceedings of the first international conference on Simulation of Adaptative Behavior (SAB). MIT Press, Cambridge (1991)Google Scholar
- 18.Weiser, M., Brown, J.S.: Designing calm technology. PowerGrid Journal 1(1) (1996)Google Scholar
- 19.Wooldridge, M.: An introduction to multi-agent systems. John Wiley & Sons, Chichester (2002)Google Scholar