Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Parallel Substitution Algorithm: Theory and Application
Parallel Substitution Algorithm: Theory and Application
CDL++ for the Description of Moving Objects in Cellular Automata
PaCT '999 Proceedings of the 5th International Conference on Parallel Computing Technologies
GCA: Global Cellular Automata. A Flexible Parallel Model
PaCT '01 Proceedings of the 6th International Conference on Parallel Computing Technologies
A Stream Processor Architecture Based on the Configurable CEPRA-S
FPL '00 Proceedings of the The Roadmap to Reconfigurable Computing, 10th International Workshop on Field-Programmable Logic and Applications
SOS++: finding smart behaviors using learning and evolution
ICAL 2003 Proceedings of the eighth international conference on Artificial life
Infinite snake tiling problems
DLT'02 Proceedings of the 6th international conference on Developments in language theory
Evolving Multi-creature Systems for All-to-All Communication
ACRI '08 Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry
Solving the exploration's problem with several creatures more efficiently
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
Optimal 6-state algorithms for the behavior of several moving creatures
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Are several creatures more efficient than a single one?
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
parallel hardware architecture to simulate movable creatures in the CA model
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
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The goal of our investigation is to find automatically the best rule for a cell in the cellular automata model. The cells are either of type Obstacle, Empty or Creature. Only Creature can move around in the cell space and can perform one of the four actions: if the path to the next cell is blocked: turn left or right, if the path is free: move ahead and simultaneously turn left or right. The task of the creature is to cross all empty cells with a minimum number of steps. The behavior was modeled using a variable state machine represented by a state table. Input to the state table is the neighbor's state in front of its moving direction. The goal is to find the absolutely best rule in the set of all possible rules. The search space grows exponentially with the number of states. As simulation, testing and evaluating the quality are very time consuming in software, the migration of the problem to a parallel hardware platform is a promising solution. In order to reduce the computation time, the search procedure was (1) implemented in hardware and (2) solutions which are equivalent under state permutations were not generated and (3) solutions which show or expect bad or trivial behavior were excluded as soon as possible in a preselection phase. Exactly six different five-state algorithms could be detected, which allow to cross all empty cells for all the given initial configurations. We described this model in Verilog HDL and in AHDL. A hardware synthesizing tool transforms the description into a configuration file which was loaded into a field programmable gate array (FPGA). Hardware implementation offers a significant speed up of many thousands compared to software.