17 found
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  1.  63
    On Computational Explanations.Anna-Mari Rusanen & Otto Lappi - 2016 - Synthese 193 (12):3931-3949.
    Computational explanations focus on information processing required in specific cognitive capacities, such as perception, reasoning or decision-making. These explanations specify the nature of the information processing task, what information needs to be represented, and why it should be operated on in a particular manner. In this article, the focus is on three questions concerning the nature of computational explanations: What type of explanations they are, in what sense computational explanations are explanatory and to what extent they involve a special, “independent” (...)
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  2.  31
    Systematic Observation of an Expert Driver's Gaze Strategy—An On-Road Case Study.Otto Lappi, Paavo Rinkkala & Jami Pekkanen - 2017 - Frontiers in Psychology 8.
  3.  4
    The Racer’s Brain – How Domain Expertise is Reflected in the Neural Substrates of Driving.Otto Lappi - 2015 - Frontiers in Human Neuroscience 9.
  4.  17
    The Racer's Mind—How Core Perceptual-Cognitive Expertise Is Reflected in Deliberate Practice Procedures in Professional Motorsport.Otto Lappi - 2018 - Frontiers in Psychology 9.
  5.  5
    Flow Experiences During Visuomotor Skill Acquisition Reflect Deviation From a Power-Law Learning Curve, but Not Overall Level of Skill.Benjamin Ultan Cowley, Jussi Palomäki, Tuisku Tammi, Roosa Frantsi, Ville-Pekka Inkilä, Noora Lehtonen, Pasi Pölönen, Juha Vepsäläinen & Otto Lappi - 2019 - Frontiers in Psychology 10.
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  6. Turing Machines and Causal Mechanisms in Cognitive Science.Otto Lappi & Anna-Mari Rusanen - 2011 - In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press. pp. 224--239.
     
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  7.  1
    Looking at the Road When Driving Around Bends: Influence of Vehicle Automation and Speed.Damien Schnebelen, Otto Lappi, Callum Mole, Jami Pekkanen & Franck Mars - 2019 - Frontiers in Psychology 10.
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  8.  8
    An Information Semantic Account of Scientific Models.Anna-Mari Rusanen & Otto Lappi - 2012 - In Henk W. de Regt (ed.), Epsa Philosophy of Science: Amsterdam 2009. Springer. pp. 315--327.
  9.  4
    Action Control, Forward Models and Expected Rewards: Representations in Reinforcement Learning.Jami Pekkanen, Jesse Kuokkanen, Otto Lappi & Anna-Mari Rusanen - 2021 - Synthese 199 (5-6):14017-14033.
    The fundamental cognitive problem for active organisms is to decide what to do next in a changing environment. In this article, we analyze motor and action control in computational models that utilize reinforcement learning algorithms. In reinforcement learning, action control is governed by an action selection policy that maximizes the expected future reward in light of a predictive world model. In this paper we argue that RL provides a way to explicate the so-called action-oriented views of cognitive systems in representational (...)
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  10.  4
    From Fly Detectors to Action Control: Representations in Reinforcement Learning.Anna-Mari Rusanen, Otto Lappi, Jami Pekkanen & Jesse Kuokkanen - 2021 - Philosophy of Science 88 (5):1045-1054.
    According to radical enactivists, cognitive sciences should abandon the representational framework. Perceptuomotor cognition and action control are often provided as paradigmatic examples of nonrepresentational cognitive phenomena. In this article, we illustrate how motor and action control are studied in research that uses reinforcement learning algorithms. Crucially, this approach can be given a representational interpretation. Hence, reinforcement learning provides a way to explicate action-oriented views of cognitive systems in a representational way.
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  11.  68
    Scientific Models as Information Carrying Artifacts.Anna-Mari Rusanen & Otto Lappi - unknown
    We present an information theoretic account of models as scientific representations, where scientific models are understood as information carrying artifacts. We propose that the semantics of models should be based on this information coupling of the model to the world. The information theoretic account presents a way of avoiding the need to refer to agents' intentions as constitutive of the semantics of scientific representations, and it provides a naturalistic account of model semantics, which can deal with the problems of asymmetry, (...)
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  12. Egocentric Chunking in the Predictive Brain: A Cognitive Basis of Expert Performance in High-Speed Sports.Otto Lappi - 2022 - Frontiers in Human Neuroscience 16.
    What principles and mechanisms allow humans to encode complex 3D information, and how can it be so fast, so accurately and so flexibly transformed into coordinated action? How do these processes work when developed to the limit of human physiological and cognitive capacity—as they are in high-speed sports, such as alpine skiing or motor racing? High-speed sports present not only physical challenges, but present some of the biggest perceptual-cognitive demands for the brain. The skill of these elite athletes is in (...)
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  13.  57
    Models as Information Carrying Artifacts.Otto Lappi & Anna-Mari Rusanen - unknown
    In science, models are used in many different ways: to test empirical hypotheses, to help in theory formation, to visualize data, and so on. Scientists construct and study the behavior of models, and compare this to observed behavior of a target system. We propose that for this to be possible models must carry information about their targets. When models are viewed as information carrying entities, this property can be used as a foundation for a representational theory of models. This account (...)
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  14.  6
    Editorial: High Performance Cognition: Information-Processing in Complex Skills, Expert Performance, and Flow.Benjamin Ultan Cowley, Frederic Dehais, Stephen Fairclough, Alexander John Karran, Jussi Palomäki & Otto Lappi - 2020 - Frontiers in Psychology 11.
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  15.  1
    Gaze Strategies in Driving–An Ecological Approach.Otto Lappi - 2022 - Frontiers in Psychology 13.
    Human performance in natural environments is deeply impressive, and still much beyond current AI. Experimental techniques, such as eye tracking, may be useful to understand the cognitive basis of this performance, and “the human advantage.” Driving is domain where these techniques may deployed, in tasks ranging from rigorously controlled laboratory settings through high-fidelity simulations to naturalistic experiments in the wild. This research has revealed robust patterns that can be reliably identified and replicated in the field and reproduced in the lab. (...)
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  16.  7
    Effect of Meditative Movement on Affect and Flow in Qigong Practitioners.Pasi Pölönen, Otto Lappi & Mari Tervaniemi - 2019 - Frontiers in Psychology 10.
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  17.  10
    Qualitative Quantitative and Experimental Concept Possession, Criteria for Identifying Conceptual Change in Science Education.Otto Lappi - 2013 - Science & Education 22 (6):1347-1359.
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