University of Helsinki
Department of Philosophy (Theoretical Philosophy, Practical Philosophy, Philosophy in Swedish)
PhD, 2015
Areas of Specialization
Philosophy, Misc
Other Academic Areas
  •  561
    Making too many enemies: Hutto and Myin’s attack on computationalism
    Philosophical Explorations 21 (2): 282-294. 2018.
    We analyse Hutto & Myin's three arguments against computationalism [Hutto, D., E. Myin, A. Peeters, and F. Zahnoun. Forthcoming. “The Cognitive Basis of Computation: Putting Computation In Its Place.” In The Routledge Handbook of the Computational Mind, edited by M. Sprevak, and M. Colombo. London: Routledge.; Hutto, D., and E. Myin. 2012. Radicalizing Enactivism: Basic Minds Without Content. Cambridge, MA: MIT Press; Hutto, D., and E. Myin. 2017. Evolving Enactivism: Basic Minds Meet Content. C…Read more
  •  98
    On computational explanations
    with Otto Lappi
    Synthese 193 (12): 3931-3949. 2016.
    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 explanati…Read more
  •  80
    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…Read more
  •  70
    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 pr…Read more
  •  49
    An Information Semantic Account of Scientific Models
    with Otto Lappi
    In Henk W. De Regt, Stephan Hartmann & Samir Okasha (eds.), EPSA Philosophy of Science: Amsterdam 2009, Springer. pp. 315--327. 2011.
  •  43
    Concepts in change
    with Samuli Pöyhönen
    Science & Education 22 (6). 2013.
    In this article we focus on the concept of concept in conceptual change. We argue that (1) theories of higher learning must often employ two different notions of concept that should not be conflated: psychological and scientific concepts. The usages for these two notions are partly distinct and thus straightforward identification between them is unwarranted. Hence, the strong analogy between scientific theory change and individual learning should be approached with caution. In addition, we argue…Read more
  •  25
    From Fly Detectors to Action Control: Representations in Reinforcement Learning
    with Otto Lappi, Jami Pekkanen, and Jesse Kuokkanen
    Philosophy of Science 88 (5): 1045-1054. 2021.
    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-o…Read more
  •  25
    Action control, forward models and expected rewards: representations in reinforcement learning
    with Jami Pekkanen, Jesse Kuokkanen, and Otto Lappi
    Synthese 199 (5-6): 14017-14033. 2021.
    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 (RL) 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 …Read more
  • Turing machines and causal mechanisms in cognitive science
    with Otto Lappi
    In Phyllis McKay Illari Federica Russo (ed.), Causality in the Sciences, Oxford University Press. pp. 224--239. 2011.