6,716 research outputs found

    Integrated information increases with fitness in the evolution of animats

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    One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

    Autonomous virulence adaptation improves coevolutionary optimization

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    Saving the mutual manipulability account of constitutive relevance

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    Constitutive mechanistic explanations are said to refer to mechanisms that constitute the phenomenon-to-be-explained. The most prominent approach of how to understand this constitution relation is Carl Craver’s mutual manipulability approach to constitutive relevance. Recently, the mutual manipulability approach has come under attack (Leuridan 2012; Baumgartner and Gebharter 2015; Romero 2015; Harinen 2014; Casini and Baumgartner 2016). Roughly, it is argued that this approach is inconsistent because it is spelled out in terms of interventionism (which is an approach to causation), whereas constitutive relevance is said to be a non-causal relation. In this paper, I will discuss a strategy of how to resolve this inconsistency, so-called fat-handedness approaches (Baumgartner and Gebharter 2015; Casini and Baumgartner 2016; Romero 2015). I will argue that these approaches are problematic. I will present a novel suggestion of how to consistently define constitutive relevance in terms of interventionism. My approach is based on a causal interpretation of mutual manipulability, where manipulability is interpreted as a causal relation between the mechanism’s components and temporal parts of the phenomenon

    When the path is never shortest: a reality check on shortest path biocomputation

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    Shortest path problems are a touchstone for evaluating the computing performance and functional range of novel computing substrates. Much has been published in recent years regarding the use of biocomputers to solve minimal path problems such as route optimisation and labyrinth navigation, but their outputs are typically difficult to reproduce and somewhat abstract in nature, suggesting that both experimental design and analysis in the field require standardising. This chapter details laboratory experimental data which probe the path finding process in two single-celled protistic model organisms, Physarum polycephalum and Paramecium caudatum, comprising a shortest path problem and labyrinth navigation, respectively. The results presented illustrate several of the key difficulties that are encountered in categorising biological behaviours in the language of computing, including biological variability, non-halting operations and adverse reactions to experimental stimuli. It is concluded that neither organism examined are able to efficiently or reproducibly solve shortest path problems in the specific experimental conditions that were tested. Data presented are contextualised with biological theory and design principles for maximising the usefulness of experimental biocomputer prototypes.Comment: To appear in: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

    Fast Escape from Quantum Mazes in Integrated Photonics

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    Escaping from a complex maze, by exploring different paths with several decision-making branches in order to reach the exit, has always been a very challenging and fascinating task. Wave field and quantum objects may explore a complex structure in parallel by interference effects, but without necessarily leading to more efficient transport. Here, inspired by recent observations in biological energy transport phenomena, we demonstrate how a quantum walker can efficiently reach the output of a maze by partially suppressing the presence of interference. In particular, we show theoretically an unprecedented improvement in transport efficiency for increasing maze size with respect to purely quantum and classical approaches. In addition, we investigate experimentally these hybrid transport phenomena, by mapping the maze problem in an integrated waveguide array, probed by coherent light, hence successfully testing our theoretical results. These achievements may lead towards future bio-inspired photonics technologies for more efficient transport and computation.Comment: 13 pages, 10 figure

    Which way do I go? Neural activation in response to feedback and spatial processing in a virtual T-maze

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    In 2 human event-related brain potential (ERP) experiments, we examined the feedback error-related negativity (fERN), an ERP component associated with reward processing by the midbrain dopamine system, and the N170, an ERP component thought to be generated by the medial temporal lobe (MTL), to investigate the contributions of these neural systems toward learning to find rewards in a "virtual T-maze" environment. We found that feedback indicating the absence versus presence of a reward differentially modulated fERN amplitude, but only when the outcome was not predicted by an earlier stimulus. By contrast, when a cue predicted the reward outcome, then the predictive cue (and not the feedback) differentially modulated fERN amplitude. We further found that the spatial location of the feedback stimuli elicited a large N170 at electrode sites sensitive to right MTL activation and that the latency of this component was sensitive to the spatial location of the reward, occurring slightly earlier for rewards following a right versus left turn in the maze. Taken together, these results confirm a fundamental prediction of a dopamine theory of the fERN and suggest that the dopamine and MTL systems may interact in navigational learning tasks
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