CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
The appeal of parallel distributed processing
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
The machine as metaphor and tool
A dynamical systems perspective on agent-environment interaction
Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
An introduction to genetic algorithms
An introduction to genetic algorithms
Computer science as empirical inquiry: symbols and search
Communications of the ACM
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Contextual Genetic Algorithms: Evolving Developmental Rules
Proceedings of the Third European Conference on Advances in Artificial Life
Semantic Closure: A Guiding Notion to Ground Artificial Life
Proceedings of the Third European Conference on Advances in Artificial Life
Artificial Life Needs a Real Epistemology
Proceedings of the Third European Conference on Advances in Artificial Life
Evolving Globally Synchronized Cellular Automata
Proceedings of the 6th International Conference on Genetic Algorithms
Mechanisms of Emergent Computation in Cellular Automata
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Genetic Algorithm Discovers Particle-Based Computation in Cellular Automata
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
The conduciveness of ca-rule graphs
Artificial Life
Hi-index | 0.00 |
We present a new definition of the concept of representation for cognitive science that is based on a study of the origin of structures that are used to store memory in evolving systems. This study consists of novel computer experiments in the evolution of cellular automata to perform nontrivial tasks as well as evidence from biology concerning genetic memory. Our key observation is that representations require inert structures to encode information used to construct appropriate dynamic configurations for the evolving system. We propose criteria to decide if a given structure is a representation by unpacking the idea of inert structures that can be used as memory for arbitrary dynamic configurations. Using a genetic algorithm, we evolved cellular automata rules that can perform nontrivial tasks related to the density task (or majority classification problem) commonly used in the literature. We present the particle catalogs of the new rules following the computational mechanics framework. We discuss if the evolved cellular automata particles may be seen as representations according to our criteria. We show that while they capture some of the essential characteristics of representations, they lack an essential one. Our goal is to show that artificial life can be used to shed new light on the computation-versus-dynamics debate in cognitive science, and indeed function as a constructive bridge between the two camps. Our definitions of representation and cellular automata experiments are proposed as a complementary approach, with both dynamics and informational modes of explanation.