David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
Review of Symbolic Logic 5 (4):574-612 (2012)
Systems of logico-probabilistic (LP) reasoning characterize inference from conditional assertions that express high conditional probabilities. In this paper we investigate four prominent LP systems, the systems O, P, Z, and QC. These systems differ in the number of inferences they licence (O ⊂ P ⊂ Z ⊂ QC). LP systems that license more inferences enjoy the possible reward of deriving more true and informative conclusions, but with this possible reward comes the risk of drawing more false or uninformative conclusions. In the first part of the paper, we present the four systems and extend each of them by theorems that allow one to compute almost-tight lower-probability-bounds for the conclusion of an inference, given lower-probability-bounds for its premises. In the second part of the paper, we investigate by means of computer simulations which of the four systems provides the best balance of reward versus risk. Our results suggest that system Z offers the best balance.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
David K. Lewis (1973). Counterfactuals. Blackwell Publishers.
Rudolf Carnap (1962). Logical Foundations of Probability. Chicago]University of Chicago Press.
Judea Pearl (1988). Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann.
Citations of this work BETA
Matthias Unterhuber & Gerhard Schurz (2014). Completeness and Correspondence in Chellas–Segerberg Semantics. Studia Logica 102 (4):891-911.
Paul D. Thorn & Gerhard Schurz (2014). A Utility Based Evaluation of Logico-Probabilistic Systems. Studia Logica 102 (4):867-890.
Similar books and articles
J. Paris & A. Vencovská (1998). Proof Systems for Probabilistic Uncertain Reasoning. Journal of Symbolic Logic 63 (3):1007-1039.
Varsha Singh & Azizuddin Khan (2009). Heterogeneity in Choices on Iowa Gambling Task: Preference for Infrequent–High Magnitude Punishment. [REVIEW] Mind and Society 8 (1):43-57.
Niki Pfeifer & G. D. Kleiter (2006). Inference in Conditional Probability Logic. Kybernetika 42 (2):391--404.
Sara Franceschelli (2009). Computer Simulations as Experiments. Synthese 169 (3):557 - 574.
Anouk Barberousse, Sara Franceschelli & Cyrille Imbert (2009). Computer Simulations as Experiments. Synthese 169 (3):557 - 574.
Ernest W. Adams (1996). Four Probability-Preserving Properties of Inferences. Journal of Philosophical Logic 25 (1):1 - 24.
Roger M. Cooke (1986). Probabilistic Reasoning in Expert Systems Reconstructed in Probability Semantics. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:409 - 421.
Elwin Myers (2010). Influence of Economic Reward and Punishment on Unethical Behavior. Business and Professional Ethics Journal 29 (1/4):155-174.
Eric A. Salzen (2000). Affect Systems and Neural Systems. Behavioral and Brain Sciences 23 (2):216-217.
Patricio O'Donnell (2005). Mesolimbic-Mesocortical Loops May Encode Saliency, Not Just Reward. Behavioral and Brain Sciences 28 (3):360-361.
Edmund T. Rolls (2000). Précis of the Brain and Emotion. Behavioral and Brain Sciences 23 (2):177-191.
Asterios G. “Stell” Kefalas (2011). On Systems Thinking and the Systems Approach. World Futures 67 (4-5):343 - 371.
Added to index2012-08-21
Total downloads44 ( #92,506 of 1,793,078 )
Recent downloads (6 months)5 ( #169,529 of 1,793,078 )
How can I increase my downloads?