Swarm Intelligence Systems Cellular Automata Christian Jacob jacob@cpsc.ucalgary.ca Global Effects from Local Rules Department of Computer Science University of Calgary Cellular Automata One-dimensional finite CA architecture The CA space is a lattice of cells with a particular geometry. Each cell contains a variable from a limited range (e.g., 0 and 1). All cells update synchronously. All cells use the same updating rule, deping only on local relations. Time advances in discrete steps. K = 5 local connections per cell Synchronous update in discrete time steps time 3 A. Wuensche: The Ghost in the Machine, Artificial Life III, 1994. 4 Cellular Automata: Local Rules Global Effects 2-D CA: Emergent Pattern Formation in Excitable Media Neuron excitation Hodgepodge 5 Neuron excitation (relaxed) 9
Swarm Systems Cellular Automata Random Boolean Networks Classifier Systems Self-organization Team work Competition... and Heavy Loads Hölldobler & Wilson, 1990 Experimental setup for studying ant foreaging behaviour Ant Foreaging and Shortest Paths Bonabeau et al., 1999 10 Ants Hölldobler & Wilson, 1990 Behaviour Learning about Emergent System Behaviours (d) and finally the shortest path emerges. (b) An obstacle is placed in the middle. Shortest Path Discovery (a) Ants walking between nest and food sites (c) Ants turn left or right, while droping pheromone...
Adaptation to Environmental Changes (a) The newly found shortest path Massively Parallel Micro Worlds StarLogo Mitchel Resnick (MIT, 1997) (b) Moving the obstacle (c) Discovery of new shortest path Agent-Based Evolution Emergent System Behaviour Simulated Massive Parallelism Interacting Agents Cooperation Competition Emergent System Behaviour Collective Foraging Equidistant Food Sites Randomly Distributed Food Sites Emergent System Behaviour to look-for-food if not carrying-food? [ifelse (ask patch-here [pheromone]) < 0.2 [right random 40 left random 40] [set-heading uphill pheromone] forward 1] to return-to-nest if carrying-food? [ask patch-here [add-pheromone-drop] set-drop-size drop-size - 0.6 set-heading uphill nest-scent forward 1] Simulated to find-food if (not carrying-food?) and ask patch-here [food > 0] [set-carrying-food? True ask patch-here [set-food food - 1] set-drop-size 35 right 180 forward 1] to find-nest if carrying-food? and ask patch-here [nest?] [set-carrying-food? False right 180 forward 1] Demo Following Behaviour
Interactions among Social Insects Interactions among Social Insects Direct Interactions Food or liquid exchange Visual or tactile, or scentuous contact Pheromones Indirect Interactions: Stigmergy Individual behaviour modifies the environment (e.g., by putting up signs = stigma), which in turn modifies the behaviour of other individuals. Demo Stigmergy in Action What to Learn from Ant Colonies as Complex Systems Fairly simple units generate complicated global behaviour. If we knew how an ant colony works, we might understand more about how all such systems work, from brains to ecosystems. (Gordon, 1999) Bonabeau et al., 1999 Emergence in Complex Systems How do neurons respond to each other in a way that produces thoughts? How do cells respond to each other in a way that produces the distinct tissues of a growing embryo? How do species interact to produce predictable changes,, over time, in ecological communities?... Swarm Systems Providing New Insights...
References Bonabeau, E., Dorigo, M., and Theraulaz, G. (1999). Swarm Intelligence: From Natural to Artificial Systems. New York, Oxford University Press. Ernst, A. M., ed. (1998). Digest: Kooperation und Konkurrenz, Heidelberg, Spektrum Akademischer Verlag. Gordon, D. (1999). Ants at Work. New York, The Free Press. Hölldobler, B., and Wilson, E. O. (1990). The Ants. Cambridge, MA, Harvard University Press. Nuridsany, C., and Pérennou, M. (1996). Microcosmos: The Invisible World of Insects. New York, Stewart, Tabori & Chang. Resnik, M. (1997). Turtles, Termites, and Traffic Jams. Cambridge, MA, MIT Press. Stevens, C. F., et al. (1988). Gehirn und Nervensystem. Heidelberg, Spektrum Akademischer Verlag.