Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures

We investigate fundamental decisions in the design of instruction set architectures for linear genetic programs that are used as both model systems in evolutionary biology and underlying solution representations in evolutionary computation. We subjected digital organisms with each tested architecture to seven different computational environments designed to present a range of evolutionary challenges. Our goal was to engineer a general purpose architecture that would be effective under a broad range of evolutionary conditions. We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow. We also tested a variety of methods to regulate expression: (4) explicit labels that allow programs to dynamically refer to specific genome positions, (5) position-relative search instructions, and (6) multiple new flow control instructions, including conditionals and jumps. Each of these features also adds complication to the instruction set and risks slowing evolution due to epistatic interactions. Two features (multiple argument specification and separated I/O) demonstrated substantial improvements int the majority of test environments. Some of the remaining tested modifications were detrimental, thought most exhibit no systematic effects on evolutionary potential, highlighting the robustness of digital evolution. Combined, these observations enhance our understanding of how instruction architecture impacts evolutionary potential, enabling the creation of architectures that support more rapid evolution of complex solutions to a broad range of challenges

Extending Kolmogorov's axioms for a generalized probability theory on collections of contexts

Kolmogorov's axioms of probability theory are extended to conditional probabilities among distinct (and sometimes intertwining) contexts. Formally, this amounts to row stochastic matrices whose entries characterize the conditional probability to find some observable (postselection) in one context, given an observable (preselection) in another context. As the respective probabilities need not (but, depending on the physical/model realization, can) be of the Born rule type, this generalizes approaches to quantum probabilities by Auff\'eves and Grangier, which in turn are inspired by Gleason's theorem.Comment: 18 pages, 3 figures, greatly revise

Dissection of a Bug Dataset: Anatomy of 395 Patches from Defects4J

Well-designed and publicly available datasets of bugs are an invaluable asset to advance research fields such as fault localization and program repair as they allow directly and fairly comparison between competing techniques and also the replication of experiments. These datasets need to be deeply understood by researchers: the answer for questions like "which bugs can my technique handle?" and "for which bugs is my technique effective?" depends on the comprehension of properties related to bugs and their patches. However, such properties are usually not included in the datasets, and there is still no widely adopted methodology for characterizing bugs and patches. In this work, we deeply study 395 patches of the Defects4J dataset. Quantitative properties (patch size and spreading) were automatically extracted, whereas qualitative ones (repair actions and patterns) were manually extracted using a thematic analysis-based approach. We found that 1) the median size of Defects4J patches is four lines, and almost 30% of the patches contain only addition of lines; 2) 92% of the patches change only one file, and 38% has no spreading at all; 3) the top-3 most applied repair actions are addition of method calls, conditionals, and assignments, occurring in 77% of the patches; and 4) nine repair patterns were found for 95% of the patches, where the most prevalent, appearing in 43% of the patches, is on conditional blocks. These results are useful for researchers to perform advanced analysis on their techniques' results based on Defects4J. Moreover, our set of properties can be used to characterize and compare different bug datasets.Comment: Accepted for SANER'18 (25th edition of IEEE International Conference on Software Analysis, Evolution and Reengineering), Campobasso, Ital

Relevant Logics Obeying Component Homogeneity

This paper discusses three relevant logics that obey Component Homogeneity - a principle that Goddard and Routley introduce in their project of a logic of significance. The paper establishes two main results. First, it establishes a general characterization result for two families of logic that obey Component Homogeneity - that is, we provide a set of necessary and sufficient conditions for their consequence relations. From this, we derive characterization results for S*fde, dS*fde, crossS*fde. Second, the paper establishes complete sequent calculi for S*fde, dS*fde, crossS*fde. Among the other accomplishments of the paper, we generalize the semantics from Bochvar, Hallden, Deutsch and Daniels, we provide a general recipe to define containment logics, we explore the single-premise/single-conclusion fragment of S*fde, dS*fde, crossS*fdeand the connections between crossS*fde and the logic Eq of equality by Epstein. Also, we present S*fde as a relevant logic of meaninglessness that follows the main philosophical tenets of Goddard and Routley, and we briefly examine three further systems that are closely related to our main logics. Finally, we discuss Routley's criticism to containment logic in light of our results, and overview some open issues

Hierarchical probabilistic macromodeling for QCA circuits

With the goal of building an hierarchical design methodology for quantum-dot cellular automata (QCA) circuits, we put forward a novel, theoretically sound, method for abstracting the behavior of circuit components in QCA circuit, such as majority logic, lines, wire-taps, cross-overs, inverters, and corners, using macromodels. Recognizing that the basic operation of QCA is probabilistic in nature, we propose probabilistic macromodels for standard QCA circuit elements based on conditional probability characterization, defined over the output states given the input states. Any circuit model is constructed by chaining together the individual logic element macromodels, forming a Bayesian network, defining a joint probability distribution over the whole circuit. We demonstrate three uses for these macromodel-based circuits. First, the probabilistic macromodels allow us to model the logical function of QCA circuits at an abstract level - the "circuit" level - above the current practice of layout level in a time and space efficient manner. We show that the circuit level model is orders of magnitude faster and requires less space than layout level models, making the design and testing of large QCA circuits efficient and relegating the costly full quantum-mechanical simulation of the temporal dynamics to a later stage in the design process. Second, the probabilistic macromodels abstract crucial device level characteristics such as polarization and low-energy error state configurations at the circuit level. We demonstrate how this macromodel-based circuit level representation can be used to infer the ground state probabilities, i.e., cell polarizations, a crucial QCA parameter. This allows us to study the thermal behavior of QCA circuits at a higher level of abstraction. Third, we demonstrate the use of these macromodels for error analysis. We show that low-energy state configurations of the macromodel circuit match those of the layout level, thus allowing us to isolate weak p- oints in circuits design at the circuit level itsel

Three-slit experiments and quantum nonlocality

An interesting link between two very different physical aspects of quantum mechanics is revealed; these are the absence of third-order interference and Tsirelson's bound for the nonlocal correlations. Considering multiple-slit experiments - not only the traditional configuration with two slits, but also configurations with three and more slits - Sorkin detected that third-order (and higher-order) interference is not possible in quantum mechanics. The EPR experiments show that quantum mechanics involves nonlocal correlations which are demonstrated in a violation of the Bell or CHSH inequality, but are still limited by a bound discovered by Tsirelson. It now turns out that Tsirelson's bound holds in a broad class of probabilistic theories provided that they rule out third-order interference. A major characteristic of this class is the existence of a reasonable calculus of conditional probability or, phrased more physically, of a reasonable model for the quantum measurement process.Comment: 9 pages, no figur