Search

Whether and how well people can behave randomly is of interest in many areas of psychological research. The ability to generate randomness is often investigated using random number generation (RNG) tasks, in which participants are asked to generate a sequence of numbers that is as random as possible. However, there is no consensus on how best to quantify the randomness of responses in human-generated sequences. Traditionally, psychologists have used measures of randomness that directly assess specific features of human behavior in RNG tasks, such as the tendency to avoid repetition or to systematically generate numbers that have not been generated in the recent choice history, a behavior known as cycling. Other disciplines have proposed measures of randomness that are based on a more rigorous mathematical foundation and are less restricted to specific features of randomness, such as algorithmic complexity. More recently, variants of these measures have been proposed to assess systematic patterns in short sequences. We report the first large-scale integrative study to compare measures of specific aspects of randomness with entropy-derived measures based on information theory and measures based on algorithmic complexity. We compare the ability of the different measures to discriminate between human-generated sequences and truly random sequences based on atmospheric noise, and provide a systematic analysis of how the usefulness of randomness measures is affected by sequence length. We conclude with recommendations that can guide the selection of appropriate measures of randomness in psychological research. [ABSTRACT FROM AUTHOR]

We study practical approximations of Kolmogorov prefix complexity (K) using IMP2, a high-level programming language. Our focus is on investigating the optimality of the interpreter for this language as the reference machine for the Coding Theorem Method (CTM). This method is designed to address applications of algorithmic complexity that differ from the popular traditional lossless compression approach based on the principles of algorithmic probability. The chosen model of computation is proven to be suitable for this task, and a comparison to other models and methods is conducted. Our findings show that CTM approximations using our model do not always correlate with the results from lower-level models of computation. This suggests that some models may require a larger program space to converge to Levin's universal distribution. Furthermore, we compare the CTM with an upper bound on Kolmogorov complexity and find a strong correlation, supporting the CTM's validity as an approximation method with finer-grade resolution of K. [ABSTRACT FROM AUTHOR]

This article investigates solving the min-max affine fractional programming problem (MAFPP), which arises in systems science and engineering. For globally solving the MAFPP, based on the outer space branching search, we design a branch-relaxation-bound algorithm. In the algorithm, we firstly convert the MAFPP into an equivalent problem with linear fractional constraints by introducing some auxiliary parameter variables. Next, to determine and update the lower bound during the branching search process, we construct the linear relaxation problem of the equivalence problem by using a new relaxation technique. The global convergence of the presented algorithm is verified. Also, by analyzing the algorithmic complexity, we give a maximum estimate of iteration times of the presented algorithm. Finally, computational comparison results are reported to demonstrate the effectiveness and feasibility of the presented algorithm. [ABSTRACT FROM AUTHOR]

We study practical approximations of Kolmogorov prefix complexity (K) using IMP2, a high-level programming language. Our focus is on investigating the optimality of the interpreter for this language as the reference machine for the Coding Theorem Method (CTM). This method is designed to address applications of algorithmic complexity that differ from the popular traditional lossless compression approach based on the principles of algorithmic probability. The chosen model of computation is proven to be suitable for this task, and a comparison to other models and methods is conducted. Our findings show that CTM approximations using our model do not always correlate with the results from lower-level models of computation. This suggests that some models may require a larger program space to converge to Levin’s universal distribution. Furthermore, we compare the CTM with an upper bound on Kolmogorov complexity and find a strong correlation, supporting the CTM’s validity as an approximation method with finer-grade resolution of K.

Copyright of Lexikos is the property of Bureau of the Woordeboek van die Afrikaanse Taal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the game of Matching Pennies, Alice and Bob each hold a penny, and at every tick of the clock they simultaneously display the head or the tail sides of their coins. If they both display the same side, then Alice wins Bob's penny; if they display different sides, then Bob wins Alice's penny. To avoid giving the opponent a chance to win, both players seem to have nothing else to do but to randomly play heads and tails with equal frequencies. However, while not losing in this game is easy, not missing an opportunity to win is not. Randomizing your own moves can be made easy. Recognizing when the opponent's moves are not random can be arbitrarily hard. The notion of randomness is central in game theory, but it is usually taken for granted. The notion of outsmarting is not central in game theory, but it is central in the practice of gaming. We pursue the idea that these two notions can be usefully viewed as two sides of the same coin. The resulting analysis suggests that the methods for strategizing in gaming and security, and for randomizing in computation, can be leveraged against each other. [ABSTRACT FROM AUTHOR]

Simple rewriting rules are used to produce alphanumeric strings that embed fractal number sequences and are directly translatable into descriptions of hydrocarbon structures of considerable complexity, featuring hierarchical schemes. Rotations of the alphanumeric strings lead to radical rearrangements of the corresponding structures, which lose their initial schemes and become much less predictable, featuring different topologies of polygonal cycles. This shows that a complex and not necessarily ordered molecular structure may nevertheless have a relatively low algorithmic complexity. The variety and versatility of reorganization in chemical topology, due to the nonlocal representation of bonds in the coding string, may have played a role in prebiotic chemistry. [ABSTRACT FROM AUTHOR]

We study bases of the lattice generated by the cycles of an undirected graph, defined as the integer linear combinations of the 0/1-incidence vectors of cycles. We prove structural results for this lattice, including explicit formulas for its dimension and determinant, and we present efficient algorithms to construct lattice bases, using only cycles as generators, in quadratic time. By algebraic considerations, we relate these results to the more general setting with coefficients from an arbitrary Abelian group. Our results generalize classical results for the vector space of cycles of a graph over the binary field to the case of an arbitrary field.

The study of the complexity of algorithms, in particular the temporal complexity, is essential in the training of the computer engineer. Both the language that is used, as well as the asymptotic analysis itself, which is the essence in the comparison of algorithms, does not articulate with the one that is traditionally applied in the subject of Sequences and numerical series, for this reason the purpose of this work is to present a didactic proposal for the subject Mathematics I that includes the necessary elements to integrate the study of sequences with algorithmic complexity using the Bachmann-Landau notation, for which the analytical program of the Programming discipline, the bibliography on algorithmic complexity and the didactics of Mathematics was studied. It was verified that the learning process when studying the topic of algorithm complexity flowed much better in the students who were the subjects of the research. [ABSTRACT FROM AUTHOR]

Information theory is a viable candidate to advance our understanding of how the brain processes information generated in the internal or external environment. With its universal applicability, information theory enables the analysis of complex data sets, is free of requirements about the data structure, and can help infer the underlying brain mechanisms. Information-theoretical metrics such as Entropy or Mutual Information have been highly beneficial for analyzing neurophysiological recordings. However, a direct comparison of the performance of these methods with well-established metrics, such as the t-test, is rare. Here, such a comparison is carried out by evaluating the novelmethod of Encoded Information with Mutual Information, Gaussian Copula Mutual Information, Neural Frequency Tagging, and t-test. We do so by applying each method to event-related potentials and event-related activity in difierent frequency bands originating from intracranial electroencephalography recordings of humans andmarmosetmonkeys. Encoded Information is a novel procedure that assesses the similarity of brain responses across experimental conditions by compressing the respective signals. Such an information-based encoding is attractive whenever one is interested in detecting where in the brain condition efiects are present. [ABSTRACT FROM AUTHOR]

This paper is devoted to the evaluation of the hardware resources of computer systems for solving a computationally expensive problem such as the calculation of the probability distributions of statistics by the second multiplicity method based on Δ -exact approximations of samples with a size of 320–1280 characters and an alphabet power of 128–256 characters. The accuracy is Δ = 10 − 5 and the total solution time should not exceed 30 days or 2.592 × 10 6 seconds for 24/7 computing. Owing to the use of the properties of the second multiplicity method, the computational complexity of the calculations can be brought within the range of 9.68 × 10 22 − 1.60 × 10 52 operations with the number of tested vectors at 6.50 × 10 23 − 1.39 × 10 50 . The solution of this problem for the specified parameters of samples during the given time requires hardware resources which cannot be provided by modern computer technology such as processors, graphics accelerators and programmable logic integrated circuits. Therefore, in this paper, we analyze the possibilities of promising quantum and photon technologies for solving the problem with the given parameters. The main advantage of quantum computer systems is the high speed of calculations for all possible parameter values. However, quantum acceleration will not be achieved to calculate the probability distributions of statistics due to the need to check all the obtained solutions. Here, the number of obtained solutions corresponds to the dimension of the problem. In addition, due to the current development level of quantum hardware components, it is impossible to create and use 120 qubit quantum computers for the solution of the considered problem. Photon computers can provide high computation speeds at low power consumptions and require the smallest number of nodes to solve the considered problem. However, unsolved problems with the physical implementation of efficient memory elements and the lack of available hardware components make the use of photon computer technologies impossible for calculating the probability distributions of statistics in the near future (5–7 years). Therefore, it is most reasonable to use hybrid computer systems containing nodes of different architectures. To solve the problem on various hardware platforms (general purpose processors, GPUs and FPGAs) and configurations of hybrid computer systems, we suggest to use the architecture-independent high-level programming language SET@L. The language combines the representation of calculations as sets and collections (based on the alternative set theory of P. Vopenka), the absolutely parallel form of the problem represented as an information graph and the paradigm of aspect-oriented programming. [ABSTRACT FROM AUTHOR]

Information theory is a viable candidate to advance our understanding of how the brain processes information generated in the internal or external environment. With its universal applicability, information theory enables the analysis of complex data sets, is free of requirements about the data structure, and can help infer the underlying brain mechanisms. Information-theoretical metrics such as Entropy or Mutual Information have been highly beneficial for analyzing neurophysiological recordings. However, a direct comparison of the performance of these methods with well-established metrics, such as the t-test, is rare. Here, such a comparison is carried out by evaluating the novel method of Encoded Information with Mutual Information, Gaussian Copula Mutual Information, Neural Frequency Tagging, and t-test. We do so by applying each method to event-related potentials and event-related activity in different frequency bands originating from intracranial electroencephalography recordings of humans and marmoset monkeys. Encoded Information is a novel procedure that assesses the similarity of brain responses across experimental conditions by compressing the respective signals. Such an information-based encoding is attractive whenever one is interested in detecting where in the brain condition effects are present.

In light of the awareness that we know little about how algorithms are perceived by groups other than those in the mainstream, this study investigates how Chinese gay men on Zhihu generate folk theories of the operation and impact of the platform algorithms. After recruiting 16 long-term users on Zhihu as informants and conducting thematic analysis, two overarching themes are identified: (1) the algorithm as evictor, supported by the users' folk theories of sidelining, disorganizing, and defaming; and (2) the algorithm as protector, supported by the users' folk theories of shielding, recognizing, and exclusive networks. Based on the empirical data collected, this study provides inspiration for understanding algorithmic complexity, and challenges the mainstream appeal to break through filter bubbles (information cocoons) by indicating its (hetero)normativity. [ABSTRACT FROM AUTHOR]

In this paper, we study the Exact Subset MultiCover problem (or ESM), which can be seen as an extension of the well-known Set Cover problem. Let (U , f) be a multiset built from set U = { e 1 , e 2 , ... , e m } and function f : U → N ⁎. ESM is defined as follows: given (U , f) and a collection S = { S 1 , S 2 , ... , S n } of n subsets of U , is it possible to find a multiset (S ′ , g) with S ′ = { S 1 ′ , S 2 ′ , ... , S n ′ } and g : S ′ → N , such that (i) S i ′ ⊆ S i for every 1 ≤ i ≤ n , and (ii) each element of U appears as many times in (U , f) as in (S ′ , g) ? We study this problem under an algorithmic viewpoint and provide diverse complexity results such as polynomial cases, NP -hardness proofs and FPT algorithms. We also study two variants of ESM : (i) Exclusive Exact Subset MultiCover (EESM), which asks that each element of U appears in exactly one subset S i ′ of S ′ ; (ii) Maximum Exclusive Exact Subset MultiCover (Max-EESM), an optimization version of EESM , which asks that a maximum number of elements of U appear in exactly one subset S i ′ of S ′. For both variants, we provide several complexity results; in particular we present a 2-approximation algorithm for Max-EESM , that we prove to be tight. For these three problems, we also provide an Integer Linear Programming (ILP) formulation. [ABSTRACT FROM AUTHOR]

We study the Maximum Zero-Sum Partition problem (or MZSP), defined as follows: given a multiset S = { a 1 , a 2 , ... , a n } of integers a i ∈ Z ⁎ (where Z ⁎ denotes the set of non-zero integers) such that ∑ i = 1 n a i = 0 , find a maximum cardinality partition { S 1 , S 2 , ... , S k } of S such that, for every 1 ≤ i ≤ k , ∑ a j ∈ S i a j = 0. Solving MZSP is useful in genomics for computing evolutionary distances between pairs of species. Our contributions are a series of algorithmic results concerning MZSP , in terms of complexity, (in)approximability, with a particular focus on the fixed-parameter tractability of MZSP with respect to either (i) the size k of the solution, (ii) the number of negative (resp. positive) values in S and (iii) the largest integer in S. [ABSTRACT FROM AUTHOR]

Sorting by Genome Rearrangements is a classic problem in Computational Biology. Several models have been considered so far, each of them defines how a genome is modeled (for example, permutations when assuming no duplicated genes, strings if duplicated genes are allowed, and/or use of signs on each element when gene orientation is known), and which rearrangements are allowed. Recently, a new problem, called Sorting by Multi-Cut Rearrangements, was proposed. It uses the k-cut rearrangement which cuts a permutation (or a string) at k ≥ 2 places and rearranges the generated blocks to obtain a new permutation (or string) of same size. This new rearrangement may model chromoanagenesis, a phenomenon consisting of massive simultaneous rearrangements. Similarly as the Double-Cut-and-Join, this new rearrangement also generalizes several genome rearrangements such as reversals, transpositions, revrevs, transreversals, and block-interchanges. In this paper, we extend a previous work based on unsigned permutations and strings to signed permutations. We show the complexity of this problem for different values of k, and that the approximation algorithm proposed for unsigned permutations with any value of k can be adapted to signed permutations. We also show a 1.5-approximation algorithm for the specific case k = 4 , as well as a generic approximation algorithm applicable for any k ≥ 5 , that always reaches constant ratio. The latter makes use of the cycle graph, a well-known structure in genome rearrangements. We implemented and tested the proposed algorithms on simulated data. [ABSTRACT FROM AUTHOR]

A semi-matching coloring of a finite simple graph G=(V,E) is a mapping ϕ from V to {1, ..., k} such that (i) every color class is an independent set, and (ii) the edge set of the graph induced by the union of any two consecutive color classes is a matching. A semi-matching coloring ϕ is a local coloring if, in addition, (iii) the union of any three consecutive color classes induces a triangle-free subgraph of G. In this paper, we give two counterexamples and one positive solution to three problems arisen in recent papers of You, Cao, Wang. In particular, we show that the local and semi-matching coloring problems are NP-complete on the class of split graphs. [ABSTRACT FROM AUTHOR]

Let G be a graph, and ℓ : E (G) → { 1 , ... , k } be a k -labelling of G , i.e. , an assignment of labels from { 1 , ... , k } to the edges of G. We say that ℓ is irregular if no two distinct vertices of G are incident to the same sum of labels. The irregularity strength of G , denoted by s (G) , is the smallest k such that irregular k -labellings of G exist. These notions were introduced in the late 1980s as an alternative way to deal with an optimisation problem where one aims at making a graph irregular by multiplying its edges in an optimal way. Since then, the irregularity strength has received a lot of attention, focusing mainly on proving bounds and investigating side aspects and variants. In this work, we consider the algorithmic complexity of determining the irregularity strength of a given graph. We prove that two close variants of this problem are NP -hard, which we suspect might indicate that the original problem is hard too. Namely, we prove that determining the distant irregularity strength, where only vertices within a certain distance are required to be incident to different sums of labels, and the multiset irregularity strength, where any two distinct vertices are required to be incident to different multisets of labels, are NP -hard problems. [ABSTRACT FROM AUTHOR]

The progressive loss of functional capacity due to aging is a serious problem that can compromise human locomotion capacity, requiring the help of an assistant and reducing independence. The NanoStim project aims to develop a system capable of performing treatment with electrostimulation at the patient's home, reducing the number of consultations. The knee angle is one of the essential attributes in this context, helping understand the patient's movement during the treatment session. This article presents a wearable system that recognizes the knee angle through IMU sensors. The hardware chosen for the wearables are low cost, including an ESP32 microcontroller and an MPU-6050 sensor. However, this hardware impairs signal accuracy in the multitasking environment expected in rehabilitation treatment. Three optimization filters with algorithmic complexity O (1) were tested to improve the signal's noise. The complementary filter obtained the best result, presenting an average error of 0.6 degrees and an improvement of 77% in MSE. Furthermore, an interface in the mobile app was developed to respond immediately to the recognized movement. The systems were tested with volunteers in a real environment and could successfully measure the movement performed. In the future, it is planned to use the recognized angle with the electromyography sensor. [ABSTRACT FROM AUTHOR]

Continuous and discrete models as well as algorithms Bressan (2007) and Finbow and MacGillivray (2009) for firefighting problems are well-studied in Theoretical Computer Science. We introduce a new, discrete, and more general framework based on a graph to study firefighting problems in various terrains. In the context of this model, we present two different firefighting problems called village protection problems, where the goal is to protect a specific set of locations and provide efficient polynomial time algorithms for their solutions. We also discuss extensions of the model. [ABSTRACT FROM AUTHOR]

Counterfactuals have become an important area of interdisciplinary interest, especially in logic, philosophy of language, epistemology, metaphysics, psychology, decision theory, and even artificial intelligence. In this study, we propose a new form of analysis for counterfactuals: analysis by algorithmic complexity. Inspired by Lewis-Stalnaker's Possible Worlds Semantics, the proposed method allows for a new interpretation of the debate between David Lewis and Robert Stalnaker regarding the Limit and Singularity assumptions. Besides other results, we offer a new way to answer the problems raised by Goodman and Quine regarding vagueness, context-dependence, and the nonmonotonicity of counterfactuals. Engaging in a dialogue with literature, this study will seek to bring new insights and tools to this debate. We hope our method of analysis can make counterfactuals more understandable in an intuitively plausible way, and a philosophically justifiable manner, aligned with the way we usually think about counterfactual propositions and our imaginative reasoning. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) as an example of electrophysiological monitoring methods has a rather long history of successful application for the diagnosis and treatment of diseases, and this success would not have been possible without effective methods of mathematical, and more recently, computer analysis. Most of these methods are based on statistics. Among the methods of EEG analysis, there is a group of methods that use different versions of Shannon's entropy estimation as a "main component" and that do not differ significantly from traditional statistical approaches. Despite the external similarity, another approach is to use the Kolmogorov-Chaitin definition of complexity and the concepts of algorithmic information dynamics. The algorithmic dynamics toolbox includes techniques (e.g., block decomposition method) that appear to be applicable to EEG analysis. The current paper is an attempt to use the block decomposition method along with the recent addition to the management of EEG data provided by machine learning, with the ultimate goal of making this data more useful to researchers and medical practitioners. [ABSTRACT FROM AUTHOR]

Abstract Counterfactuals have become an important area of interdisciplinary interest, especially in logic, philosophy of language, epistemology, metaphysics, psychology, decision theory, and even artificial intelligence. In this study, we propose a new form of analysis for counterfactuals: analysis by algorithmic complexity. Inspired by Lewis-Stalnaker's Possible Worlds Semantics, the proposed method allows for a new interpretation of the debate between David Lewis and Robert Stalnaker regarding the Limit and Singularity assumptions. Besides other results, we offer a new way to answer the problems raised by Goodman and Quine regarding vagueness, context-dependence, and the non- monotonicity of counterfactuals. Engaging in a dialogue with literature, this study will seek to bring new insights and tools to this debate. We hope our method of analysis can make counterfactuals more understandable in an intuitively plausible way, and a philosophically justifiable manner, aligned with the way we usually think about counterfactual propositions and our imaginative reasoning.

This paper is devoted to the evaluation of the hardware resources of computer systems for solving a computationally expensive problem such as the calculation of the probability distributions of statistics by the second multiplicity method based on Δ-exact approximations of samples with a size of 320–1280 characters and an alphabet power of 128–256 characters. The accuracy is Δ=10−5 and the total solution time should not exceed 30 days or 2.592×106 seconds for 24/7 computing. Owing to the use of the properties of the second multiplicity method, the computational complexity of the calculations can be brought within the range of 9.68×1022−1.60×1052 operations with the number of tested vectors at 6.50×1023−1.39×1050. The solution of this problem for the specified parameters of samples during the given time requires hardware resources which cannot be provided by modern computer technology such as processors, graphics accelerators and programmable logic integrated circuits. Therefore, in this paper, we analyze the possibilities of promising quantum and photon technologies for solving the problem with the given parameters. The main advantage of quantum computer systems is the high speed of calculations for all possible parameter values. However, quantum acceleration will not be achieved to calculate the probability distributions of statistics due to the need to check all the obtained solutions. Here, the number of obtained solutions corresponds to the dimension of the problem. In addition, due to the current development level of quantum hardware components, it is impossible to create and use 120 qubit quantum computers for the solution of the considered problem. Photon computers can provide high computation speeds at low power consumptions and require the smallest number of nodes to solve the considered problem. However, unsolved problems with the physical implementation of efficient memory elements and the lack of available hardware components make the use of photon computer technologies impossible for calculating the probability distributions of statistics in the near future (5–7 years). Therefore, it is most reasonable to use hybrid computer systems containing nodes of different architectures. To solve the problem on various hardware platforms (general purpose processors, GPUs and FPGAs) and configurations of hybrid computer systems, we suggest to use the architecture-independent high-level programming language SET@L. The language combines the representation of calculations as sets and collections (based on the alternative set theory of P. Vopenka), the absolutely parallel form of the problem represented as an information graph and the paradigm of aspect-oriented programming.

In this work we deal with the so-called path convexities, defined over special collections of paths. For example, the collection of the shortest paths in a graph is associated with the well-known geodesic convexity, while the collection of the induced paths is associated with the monophonic convexity; and there are many other examples. Besides reviewing the path convexities in the literature, we propose a general path convexity framework, of which most existing path convexities can be viewed as particular cases. Some benefits of the proposed framework are the systematization of the algorithmic study of related problems and the possibility of defining new convexities not yet investigated. [ABSTRACT FROM AUTHOR]

Fuzz testing repeatedly assails software with random inputs in order to trigger unexpected program behaviors, such as crashes or timeouts, and has historically revealed serious security vulnerabilities. In this article, we present HotFuzz, a framework for automatically discovering Algorithmic Complexity (AC) time and space vulnerabilities in Java libraries. HotFuzz uses micro-fuzzing, a genetic algorithm that evolves arbitrary Java objects in order to trigger the worst-case performance for a method under test. We define Small Recursive Instantiation (SRI) as a technique to derive seed inputs represented as Java objects to micro-fuzzing. After micro-fuzzing, HotFuzz synthesizes test cases that triggered AC vulnerabilities into Java programs and monitors their execution in order to reproduce vulnerabilities outside the fuzzing framework. HotFuzz outputs those programs that exhibit high resource utilization as witnesses for AC vulnerabilities in a Java library. We evaluate HotFuzz over the Java Runtime Environment (JRE), the 100 most popular Java libraries on Maven, and challenges contained in the DARPA Space and Time Analysis for Cybersecurity (STAC) program. We evaluate SRI's effectiveness by comparing the performance of micro-fuzzing with SRI, measured by the number of AC vulnerabilities detected, to simply using empty values as seed inputs. In this evaluation, we verified known AC vulnerabilities, discovered previously unknown AC vulnerabilities that we responsibly reported to vendors, and received confirmation from both IBM and Oracle. Our results demonstrate that micro-fuzzing finds AC vulnerabilities in real-world software, and that micro-fuzzing with SRI-derived seed inputs outperforms using empty values in both the temporal and spatial domains. [ABSTRACT FROM AUTHOR]

Experimental studies of the cultural evolution of languagehave focused on how constraints on learning andcommunication drive emergence of linguistic structure. Yetlanguage is typically transmitted by experts who adjust theinput in ways that facilitates learning by novices, e.g. throughchild-directed speech. Using iterated language learning ofbinary auditory sequences, we explored how language changeis affected by experts’ intention to teach the language tonovices. Comparison between teaching chains and simpletransmission chains revealed that teaching was associatedwith a greater rate of innovation which led to emergence ofmore expressive languages consisting of shorter signals. Thisis the first study to show that during cultural transmission,teaching can modify, and potentially optimise, functionalcharacteristics of language.

It is often claimed that one cannot locate a notion of causation in fundamental physical theories. The reason most commonly given is that the dynamics of those theories do not support any distinction between the past and the future, and this vitiates any attempt to locate a notion of causal asymmetry—and thus of causation—in fundamental physical theories. I argue that this is incorrect: the ubiquitous generation of entanglement between quantum systems grounds a relevant asymmetry in the dynamical evolution of quantum systems. I show that by exploiting a connection between the amount of entanglement in a quantum state and the algorithmic complexity of that state, one can use recently developed tools for causal inference to identify a causal asymmetry—and a notion of causation—in the dynamical evolution of quantum systems. [ABSTRACT FROM AUTHOR]

Biological systems are notorious for complex behavior within short timescales (e.g., metabolic activity) and longer timescales (e.g., evolutionary selection), along with their complex spatial organization. Because of their complexity and their ability to innovate with respect to their environment, living systems are considered to be open-ended. Historically, it has been difficult to model open-ended evolution and innovation. As a result, our understanding of the exact mechanisms that distinguish open-ended living systems from nonliving ones is limited. One of the biggest barriers is understanding how multiple, complex parts within a single system interact and contribute to the complex, emergent behavior of the system as a whole. How do interactions between parts of a system lead to more complex behavior of the system as a whole? This paper presents two interacting cellular automata (CAs) as an abstract model to address the effects of complex interactions between two individual entities embedded within a larger system. Unlike elementary CAs, each cellular automaton (CA) changes its update rules as a function of the system's state as a whole. The resulting behavior of the two-CA system suggests that complex interaction functions between the two CAs have little to no effect on the complexity of each individual CA's behavior and structure. However, having an interaction function that is random results in open-ended evolution regardless of the specific type of state-dependency. [ABSTRACT FROM AUTHOR]