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AGI & CoCoSci

837 items from yuzheshi/awesome-agi-cocosci ★398

  1. Answer Set Programming link.springer.com

    ICLPNR'99, 1999. [All Versions]. [Preprint]. The original paper on Answer Set Programming (ASP), a form of declarative programming oriented towards difficult search problems, on the use of nonmonotonic reasoning in knowledge representation. In ASP solutions to a problem are…

  2. Abduction in Logic Programming link.springer.com

    Computational Logic, 2002. [All Versions]. [Preprint]. Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer…

  3. Action Languages, Answer Sets, and Planning link.springer.com

    The Logic Programming Paradigms, 1999. [All Versions]. [Preprint]. This is a discussion of some of the achievements and challenges related to representing actions and the design of planners from the perspective of logic programming. The authors talk about recent work on action…

  4. Abduction, Induction, and Analogy link.springer.com

    Model-Based Reasoning in Science and Technology, 2010. [All Versions]. The distinctions and relations between Abduction, Induction, and Analogy.

  5. VisualCOMET: Reasoning About the Dynamic Context of a Still Image link.springer.com

    ECCV'20, 2020. [All Versions].

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  6. Towards a theory of commonsense visual reasoning link.springer.com

    FSTTCS, 1990. [All Versions]. The original paper on visual commonsense.

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  7. Abductive Reasoning and Learning link.springer.com

    Springer, 2000. [All Versions]. This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches.

  8. Abductive Cognition: The Epistemological and Eco-Cognitive Dimensions of Hypothetical Reasoning link.springer.com

    Springer, 2009. [All Versions]. Most philosophers of science in the twentieth century have concluded that no logic of creative processes exists and, moreover, that a rational model of discovery is impossible. In short, scientific creative inferences are irrational and there is…

  9. A computational process-tracing method for measuring people’s planning strategies and how they change over time link.springer.com

    Behavior Research Methods, 2022. [All Versions]. Model-based strategy identification.

  10. When to trust the data: Further investigations of system error in a scientific reasoning task link.springer.com

    Memory & Cognition, 1996. [All Versions]. When evaluating experimental evidence, how do people deal with the possibility that some of the feedback is erroneous? The potential for error means that evidence evaluation must include decisions about when to “trust the data.” This…

  11. Logics for Epistemic Programs link.springer.com

    Synthese, 2004. [All Versions].

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  12. Filters, random fields and maximum entropy (FRAME): Towards a unified theory for texture modeling link.springer.com

    International Journal of Computer Vision, 1998. [All Versions]. [Preprint]. This article presents a statistical theory for texture modeling. This theory combines filtering theory and Markov random field modeling through the maximum entropy principle, and interprets and…

  13. How do people generalize causal relations over objects? A non-parametric Bayesian account link.springer.com

    Computational Brain & Behavior, 2022. [All Versions]. [Preprint]. How do people decide how general a causal relationship is, in terms of the entities or situations it applies to? What features do people use to decide whether a new situation is governed by a new causal law or an…

  14. Pragmatic Inference and Visual Abstraction Enable Contextual Flexibility During Visual Communication link.springer.com

    Computational Brain & Behavior, 2020. [All Versions]. A computational account on the rational behavior in graphical language games.

  15. Do People Ask Good Questions? link.springer.com

    Computational Brain & Behavior, 2018. [All Versions].

  16. From intention to implementation: automating biomedical research via LLMs link.springer.com

    Science China Information Sciences, 2025. [All Versions]. Conventional biomedical research is increasingly labor-intensive due to the exponential growth of scientific literature and datasets. Artificial intelligence (AI), particularly large language models (LLMs), has the…

  17. Abductive learning: towards bridging machine learning and logical reasoning link.springer.com

    Science China Information Sciences, 2019. [All Versions].

  18. Structured Generative Models for Scene Understanding link.springer.com

    International Journal of Computer Vision, 2025. [All Versions]. This position paper argues for the use of structured generative models (SGMs) for the understanding of static scenes. This requires the reconstruction of a 3D scene from an input image (or a set of multi-view…

  19. Configurable 3D Scene Synthesis and 2D Image Rendering with Per-pixel Ground Truth Using Stochastic Grammars link.springer.com

    International Journal of Computer Vision, 2018. [All Versions]. [Preprint]. This work proposes a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D images thereof, with associated ground…

  20. Abductive inference within a pragmatic framework link.springer.com

    Synthese, 2018. [All Versions].

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  21. Patterns of abduction link.springer.com

    Synthese, 2007. [All Versions]. A categorization for Abduction in the account of pure philosophy.

  22. A domain‑specifc language framework for farm management information systems in precision agriculture link.springer.com

    Precision Agriculture, 2020. [All Versions]. This paper proposes a domain-specific language framework for the design and development of precision-agriculture FMISs, which copes with challenges on supporting the understandability, enhancing communication and analysis of the…

  23. When Lingens meets Frege: communication without common ground link.springer.com

    Philosophical Studies, 2021. [All Versions].

  24. Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework link.springer.com

    Machine Learning, 2022. [All Versions]. A neuro-symbolic framework that integrates meta-policy learning in inductive logic programming.

  25. Scenic: a language for scenario specification and data generation link.springer.com

    Machine Learning, 2022. [All Versions]. This paper proposes a domain-specific language, Scenic, for describing scenarios that are distributions over scenes and the behaviors of their agents over time. Scenic combines concise, readable syntax for spatiotemporal relationships…

  26. Meta-Interpretive Learning from noisy images link.springer.com

    Machine Learning, 2018. [All Versions].

  27. Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP link.springer.com

    Machine Learning, 2018. [All Versions]. During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses. Since predictive accuracy was readily measurable and comprehensibility not…

  28. Relational affordances for multiple-object manipulation link.springer.com

    Autonomous Robots, 2017. [All Versions].

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  29. Toward understanding the importance of gesture in distributed scientific collaboration link.springer.com

    Knowledge and Information Systems, 2006. [All Versions].

  30. Comparability of automated human induced pluripotent stem cell culture: a pilot study link.springer.com

    Bioprocess and Biosystems Engineering, 2016. [All Versions].

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  31. Disjunctive Abduction link.springer.com

    New Generation Computing, 2019. [All Versions].

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  32. Pareto optimality in multiobjective problems link.springer.com

    Applied Mathematics and Optimization, 1977. [All Versions]. The original paper on the pareto optimality in multiobjective problems.

  33. Gestalt Psychology link.springer.com

    Psychologische Forschung, 1967. [All Versions]. Wolfgang Köhler's review on Gestalt psychology.

  34. Learning to perceive and act by trial and error link.springer.com

    Machine Learning, 1991. [All Versions].

  35. Beneficial and harmful explanatory machine learning link.springer.com

    Machine Learning, 2021. [All Versions]. Given the recent successes of Deep Learning in AI there has been increased interest in the role and need for explanations in machine learned theories. A distinct notion in this context is that of Michie’s definition of ultra-strong…

  36. The uses of argument library.lol

    Cambridge University Press, 1958. [All Versions]. Stephen Toulmin's introduction to the Toulmin argument pattern, which is generally consist of a claim, a justification, and a rebuttal.

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  37. Words, thoughts, and theories library.lol

    MIT Press, 1997. [All Versions]. Alison Gopnik's book that articulates and defends the "theory theory" of cognitive and semantic development, the idea that infants and young children, like scientists, learn about the world by forming and revising theories-a view of the origins…

  38. Individual differences among deep neural network models kriegeskortelab.zuckermaninstitute.columbia.edu

    Nature Communications, 2020. [All Versions].

  39. Human-level control through deep reinforcement learning klab.tch.harvard.edu

    Nature, 2015. [All Versions]. The original paper on solving Atari games via Deep Q-Network.

  40. From information scaling of natural images to regimes of statistical models jstor.org

    Quarterly of Applied Mathematics, 2008. [All Versions]. [Preprint]. One fundamental property of natural image data that distinguishes vision from other sensory tasks such as speech recognition is that scale plays a profound role in image formation and interpretation…

  41. A tagmemic approach to paragraph analysis jstor.org

    College Composition and Communication, 1965. [All Versions]. The original paper on analyzing the structure of expository paragraphs, with the two patterns---the Topic-Restriction-Illustration pattern and the Problem-Solution pattern.

  42. A Bayesian Analysis of Some Non-parametric Problems jstor.org

    The Annals of Statistics, 1973. [All Versions]. [Preprint]. A classic review on non-parametric problems.

  43. Defending Abduction journals.uchicago.edu

    Philosophy of Science, 1999. [All Versions].

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