journal article
LitStream Collection
Home
doi: 10.1007/s11047-019-09738-6pmid: N/A
Modern computers allow a methodical search of possibly billions of experiments and the exploitation of interactions that are not known in advance. This enables a bottom-up process of design by assembling or configuring systems and testing the degree to which they fulfill the desired goal. We give two detailed examples of this process. One is referred to as Cartesian genetic programming and the other evolution-in-materio. In the former, evolutionary algorithms are used to exploit the interactions of software components representing mathematical, logical, or computational elements. In the latter, evolutionary algorithms are used to manipulate physical systems particularly at the electrical or electronic level. We compare and contrast both approaches and discuss possible new research directions by borrowing ideas from one and using them in the other.
Chalk, Cameron; Martinez, Eric; Schweller, Robert; Vega, Luis; Winslow, Andrew; Wylie, Tim
doi: 10.1007/s11047-019-09740-ypmid: N/A
We analyze the complexity of building linear assemblies, sets of linear assemblies, and $${\mathcal{O}}(1)$$ O ( 1 ) -scale general shapes in the staged tile assembly model. For systems with at most b bins and t tile types, we prove that the minimum number of stages to uniquely assemble a $$1 \times n$$ 1 × n line is $$\varTheta (\log _t{n} + \log _b{\frac{n}{t}} + 1)$$ Θ ( log t n + log b n t + 1 ) . Generalizing to $${\mathcal{O}}(1) \times n$$ O ( 1 ) × n lines, we prove the minimum number of stages is $${\mathcal{O}}(\frac{\log {n} - tb - t\log t}{b^2} + \frac{\log \log b}{\log t})$$ O ( log n - t b - t log t b 2 + log log b log t ) and $$\varOmega (\frac{\log {n} - tb - t\log t}{b^2})$$ Ω ( log n - t b - t log t b 2 ) . We also obtain similar upper and lower bounds in a model permitting flexible glues using non-diagonal glue functions. Next, we consider assembling sets of lines and general shapes using $$t = {\mathcal{O}}(1)$$ t = O ( 1 ) tile types. We prove that the minimum number of stages needed to assemble a set of k lines of size at most $${\mathcal{O}}(1) \times n$$ O ( 1 ) × n is $${\mathcal{O}}(\frac{k\log n}{b^2}+\frac{k\sqrt{\log n}}{b}+\log \log n)$$ O ( k log n b 2 + k log n b + log log n ) and $$\varOmega (\frac{k\log n}{b^2})$$ Ω ( k log n b 2 ) . In the case that $$b = \mathcal {O}(\sqrt{k})$$ b = O ( k ) , the minimum number of stages is $$\varTheta (\log {n})$$ Θ ( log n ) . The upper bound in this special case is then used to assemble “hefty” shapes of at least logarithmic edge-length-to-edge-count ratio at $$\mathcal {O}(1)$$ O ( 1 ) -scale using $$\mathcal {O}(\sqrt{k})$$ O ( k ) bins and optimal $$\mathcal {O}(\log {n})$$ O ( log n ) stages.
Crowder, Tanner; Lanzagorta, Marco
doi: 10.1007/s11047-019-09737-7pmid: N/A
Using an imperfectly prepared state, we show that in relativistic settings, the evolution of a massive spin-1/2 particle violates many standard assumptions made in quantum information theory, including complete positivity. Unlike other recent endeavors in relativistic quantum information, we are able to quantify and maximize how much information can be transferred through such a quantum process by calculating its scope. We show that, surprisingly, relativistic noise can increase the amount of information that can be transferred, and in fact, even if the initial state is arbitrarily close to the completely mixed state, information can still be transferred perfectly. Additionally, we explore the relativistic effects of velocity and gravity on quantum information processing, and we briefly discuss how quantum computation is affected by general relativity. In particular, we show that the large Wigner rotation caused by a black hole as described in the Schwarzchild metric can greatly increase the informatic content of a qubit.
Fernau, Henning; Kuppusamy, Lakshmanan; Raman, Indhumathi
doi: 10.1007/s11047-019-09742-wpmid: N/A
Insertion–deletion (or ins–del for short) systems are simple models of bio-inspired computing. They are well studied in formal language theory, especially regarding their computational completeness. This concerns the question if all recursively enumerable languages can be generated. This ultimately addresses the question if one can build general-purpose computers rooted in this formalism. The descriptional complexity of an ins–del system is typically measured by its size, a 6-dimensional tuple of non-negative integers $$(e,e',e'';d,d',d'')$$ ( e , e ′ , e ′ ′ ; d , d ′ , d ′ ′ ) where e is the maximum length of the insertion string, $$e'$$ e ′ (and $$e''$$ e ′ ′ ) is the maximum length of the left (and right) context used for insertion; the last three parameters $$d,d',d''$$ d , d ′ , d ′ ′ are similarly understood for deletion rules. Computational completeness for ins–del systems can even be achieved with rule size (1, 1, 1; 1, 1, 1) but with no rule size strictly smaller than this. This fact has motivated to study ins–del systems in combination with regulation mechanisms. In this context, the six-tuple explained above is called the ID size of a system. Several regulations like graph-control, matrix and semi-conditional have been imposed on ins–del systems. Typically, the computational completeness results are obtained as trade-offs, reducing the ID size, say, to (1, 1, 0; 1, 1, 0) at the expense of increasing other measures of descriptional complexity. In this paper, we study simple semi-conditional ins–del systems, where an ins–del rule can be applied only in the presence or absence of substrings of the derivation string. This brings along two further natural parameters to measure descriptional complexity, namely, the maximum permitting string length p and the maximum forbidden string length f, usually summarized as the degree $$d=(p,f)$$ d = ( p , f ) . We show that simple semi-conditional ins–del systems of degree (2, 1) and with ID sizes $$(1+e,e',e'';1+d,d',d'')$$ ( 1 + e , e ′ , e ′ ′ ; 1 + d , d ′ , d ′ ′ ) are computationally complete for any $$e,e',e'',d,d',d''\in \{0,1\}$$ e , e ′ , e ′ ′ , d , d ′ , d ′ ′ ∈ { 0 , 1 } , with $$e+e'+e''=1$$ e + e ′ + e ′ ′ = 1 and $$d+d'+d''=1$$ d + d ′ + d ′ ′ = 1 . The obtained results complement and improve on the existing results known from the literature. To prove our results, we also show a new normal form for type-0 grammars that appears to be interesting in its own right.
Vantuch, Tomáš; Zelinka, Ivan; Adamatzky, Andrew; Marwan, Norbert
doi: 10.1007/s11047-019-09741-xpmid: N/A
Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and artificial neural networks. We demonstrate that swarm optimization algorithms also exhibit transitions from chaos, analogous to a motion of gas molecules, when particles explore solution space disorderly, to order, when particles follow a leader, similar to molecules propagating along diffusion gradients in liquid solutions of reagents. We analyze these ‘phase-like’ transitions in swarm optimization algorithms using recurrence quantification analysis and Lempel-Ziv complexity estimation. We demonstrate that converging iterations of the optimization algorithms are statistically different from non-converging ones in a view of applied chaos, complexity and predictability estimating indicators. An identification of a key factor responsible for the intensity of their phase transition is the main contribution of this paper. We examined an optimization as a process with three variable factors—an algorithm, number generator and optimization function. More than 9000 executions of the optimization algorithm revealed that the nature of an applied algorithm itself is the main source of the phase transitions. Some of the algorithms exhibit larger transition-shifting behavior while others perform rather transition-steady computing. These findings might be important for future extensions of these algorithms.
Alhazov, Artiom; Freund, Rudolf; Ivanov, Sergiu
doi: 10.1007/s11047-019-09747-5pmid: N/A
We introduce new possibilities to control the application of rules based on the preceding applications, which can be defined in a general way for (hierarchical) P systems and the main known derivation modes. Computational completeness can be obtained even with non-cooperative rules and using both activation and blocking of rules, especially for the set modes of derivation, when allowing derivation steps with no rules being applied. When we allow the application of rules to influence the application of rules in previous derivation steps, applying a non-conservative semantics for what we consider to be a valid infinite derivation, we can even “go beyond Turing”.
doi: 10.1007/s11047-018-9724-8pmid: N/A
In the original publication, Acknowledgments was published incorrectly. The correct Acknowledgments is provided in this correction.
Showing 1 to 9 of 9 Articles