Switch to: References

Add citations

You must login to add citations.
  1. Tractability and the computational mind.Rineke Verbrugge & Jakub Szymanik - 2018 - In Mark Sprevak & Matteo Colombo (eds.), The Routledge Handbook of the Computational Mind. Routledge. pp. 339-353.
    We overview logical and computational explanations of the notion of tractability as applied in cognitive science. We start by introducing the basics of mathematical theories of complexity: computability theory, computational complexity theory, and descriptive complexity theory. Computational philosophy of mind often identifies mental algorithms with computable functions. However, with the development of programming practice it has become apparent that for some computable problems finding effective algorithms is hardly possible. Some problems need too much computational resource, e.g., time or memory, to (...)
    Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Parameterized Complexity of Theory of Mind Reasoning in Dynamic Epistemic Logic.Iris van de Pol, Iris van Rooij & Jakub Szymanik - 2018 - Journal of Logic, Language and Information 27 (3):255-294.
    Theory of mind refers to the human capacity for reasoning about others’ mental states based on observations of their actions and unfolding events. This type of reasoning is notorious in the cognitive science literature for its presumed computational intractability. A possible reason could be that it may involve higher-order thinking. To investigate this we formalize theory of mind reasoning as updating of beliefs about beliefs using dynamic epistemic logic, as this formalism allows to parameterize ‘order of thinking.’ We prove that (...)
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  • Logics and collaboration.Liz Sonenberg - 2023 - Logic Journal of the IGPL 31 (6):1024-1046.
    Since the early days of artificial intelligence (AI), many logics have been explored as tools for knowledge representation and reasoning. In the spirit of the Crossley Festscrift and recognizing John Crossley’s diverse interests and his legacy in both mathematical logic and computer science, I discuss examples from my own research that sit in the overlap of logic and AI, with a focus on supporting human–AI interactions.
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  • Advances in Experimental Philosophy of Logic and Mathematics: A. Aberdein and M. Inglis, editors, London: Bloomsbury Academic, 2019. 291 pp. $28.76. ISBN 978-1-3500-3902-5.Yuri Sato - 2021 - History and Philosophy of Logic 43 (3):305-307.
    This book is a collection of articles on research that attempts to connect logic and mathematics with empirical and cognition. There have been various such a...
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark  
  • Strategic Reasoning: Building Cognitive Models from Logical Formulas.Sujata Ghosh, Ben Meijering & Rineke Verbrugge - 2014 - Journal of Logic, Language and Information 23 (1):1-29.
    This paper presents an attempt to bridge the gap between logical and cognitive treatments of strategic reasoning in games. There have been extensive formal debates about the merits of the principle of backward induction among game theorists and logicians. Experimental economists and psychologists have shown that human subjects, perhaps due to their bounded resources, do not always follow the backward induction strategy, leading to unexpected outcomes. Recently, based on an eye-tracking study, it has turned out that even human subjects who (...)
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  • Studying strategies and types of players: experiments, logics and cognitive models.Sujata Ghosh & Rineke Verbrugge - 2018 - Synthese 195 (10):4265-4307.
    How do people reason about their opponent in turn-taking games? Often, people do not make the decisions that game theory would prescribe. We present a logic that can play a key role in understanding how people make their decisions, by delineating all plausible reasoning strategies in a systematic manner. This in turn makes it possible to construct a corresponding set of computational models in a cognitive architecture. These models can be run and fitted to the participants’ data in terms of (...)
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  • Exploring the tractability border in epistemic tasks.Cédric Dégremont, Lena Kurzen & Jakub Szymanik - 2014 - Synthese 191 (3):371-408.
    We analyse the computational complexity of comparing informational structures. Intuitively, we study the complexity of deciding queries such as the following: Is Alice’s epistemic information strictly coarser than Bob’s? Do Alice and Bob have the same knowledge about each other’s knowledge? Is it possible to manipulate Alice in a way that she will have the same beliefs as Bob? The results show that these problems lie on both sides of the border between tractability (P) and intractability (NP-hard). In particular, we (...)
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  • How much does it help to know what she knows you know? An agent-based simulation study.Harmen de Weerd, Rineke Verbrugge & Bart Verheij - 2013 - Artificial Intelligence 199-200 (C):67-92.
  • You better play 7: mutual versus common knowledge of advice in a weak-link experiment.Giovanna Devetag, Hykel Hosni & Giacomo Sillari - 2013 - Synthese 190 (8):1351-1381.
    This paper presents the results of an experiment on mutual versus common knowledge of advice in a two-player weak-link game with random matching. Our experimental subjects play in pairs for thirteen rounds. After a brief learning phase common to all treatments, we vary the knowledge levels associated with external advice given in the form of a suggestion to pick the strategy supporting the payoff-dominant equilibrium. Our results are somewhat surprising and can be summarized as follows: in all our treatments both (...)
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  • The developmental paradox of false belief understanding: a dual-system solution.L. C. De Bruin & A. Newen - 2014 - Synthese 191 (3).
    We explore the developmental paradox of false belief understanding. This paradox follows from the claim that young infants already have an understanding of false belief, despite the fact that they consistently fail the elicited-response false belief task. First, we argue that recent proposals to solve this paradox are unsatisfactory because they (i) try to give a full explanation of false belief understanding in terms of a single system, (ii) fail to provide psychological concepts that are sufficiently fine-grained to capture the (...)
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   14 citations  
  • Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.Burcu Arslan, Niels A. Taatgen & Rineke Verbrugge - 2017 - Frontiers in Psychology 8.
  • Proceedings of the Workshop 'Reasoning about other minds: Logical and cognitive perspectives.J. van Eijck & R. Verbrugge (eds.) - 2011 - WEUR Proceedings.
    In recent years, the human ability to reasoning about mental states of others in order to explain and predict their behavior has come to be a highly active area of research. Researchers from a wide range of fields { from biology and psychology through linguistics to game theory and logic{ contribute new ideas and results. This interdisciplinary workshop, collocated with the Thirteenth International Conference on Theoretical Aspects of Rationality and Knowledge (TARK XIII), aims to shed light on models of social (...)
    Direct download  
     
    Export citation  
     
    Bookmark  
  • A Computational Learning Semantics for Inductive Empirical Knowledge.Kevin T. Kelly - 2014 - In Alexandru Baltag & Sonja Smets (eds.), Johan van Benthem on Logic and Information Dynamics. Springer International Publishing. pp. 289-337.
    This chapter presents a new semantics for inductive empirical knowledge. The epistemic agent is represented concretely as a learner who processes new inputs through time and who forms new beliefs from those inputs by means of a concrete, computable learning program. The agent’s belief state is represented hyper-intensionally as a set of time-indexed sentences. Knowledge is interpreted as avoidance of error in the limit and as having converged to true belief from the present time onward. Familiar topics are re-examined within (...)
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   2 citations