This work proposes quantum versions of finite-state and push-down automata, and regular and context-free grammars, and finds analogs of several classical theorems, including pumping lemmas, closure properties, rational and algebraic generating functions, and Greibach normal form.Expand

Abstract Defining structure and detecting the emergence of complexity in nature are inherently subjective, though essential, scientific activities. Despite the difficulties, these problems can be… Expand

The results quantify the extent to which populations evolve mutational robustness-the insensitivity of the phenotype to mutations-and thus reduce genetic load.Expand

An experiment similar to one performed by Packard (1988), in which a genetic algorithm is used to evolve cellular automata to perform a particular computational task, demonstrates how symmetry breaking can impede the evolution toward higher computational capability.Expand

Abstract We present results from experiments in which a genetic algorithm (GA) was used to evolve cellular automata (CAs) to perform a particular computational task - one-dimensional density… Expand

It is shown that the causal-state representation—an ∈-machine—is the minimal one consistent with accurate prediction, and several results are established on ∉-machine optimality and uniqueness and on how∈-machines compare to alternative representations.Expand

Several phenomenological approaches to applying information theoretic measures of randomness and memory to stochastic and deterministic processes are synthesized by using successive derivatives of the Shannon entropy growth curve to look at the relationships between a process's entropy convergence behavior and its underlying computational structure.Expand

Understanding how globally coordinated computation can emerge in evolution is relevant both for the scientific understanding of natural information processing and for engineering new forms of parallel computing systems.Expand

A reliable procedure for building the minimal set of hidden, Markovian states that is statistically capable of producing the behavior exhibited in the data -- the underlying process's causal states.Expand