Ideal Learning Machines. - Daniel N. Osherson; Michael Stob; Scott Weinstein (Cogn. Sci., 1982)

Learning Strategies - Daniel N. Osherson; Michael Stob; Scott Weinstein (Inf. Control., 1982)

Criteria of Language Learning - Daniel N. Osherson; Scott Weinstein (Inf. Control., 1982)

Formal Theories of Language Acquisition: Practical and Theoretical Perspectives. - Daniel N. Osherson; Michael Stob; Scott Weinstein (IJCAI, 1983)

Conceptual Combination with Prototype Concepts. - Edward E. Smith; Daniel N. Osherson (Cogn. Sci., 1984)

Identification in the limit of first order structures. - Daniel N. Osherson; Scott Weinstein (J. Philos. Log., 1986)

Aggregating Inductive Expertise - Daniel N. Osherson; Michael Stob; Scott Weinstein (Inf. Control., 1986)

Cognitive science in Europe - a report from the FAST programme of the Commission of the European Communities. - Michel Imbert; Paul Bertelson; Ruth Kempson; Daniel N. Osherson; Helmut Schnelle; Norbert A. Streitz; Arnold Thomassen; Paolo Viviani (Springer, 1987)

Combining Prototypes: A Selective Modification Model. - Edward E. Smith; Daniel N. Osherson; Lance J. Rips; Margaret Keane (Cogn. Sci., 1988)

Mechanical Learners Pay a Price for Bayesianism. - Daniel N. Osherson; Michael Stob; Scott Weinstein (J. Symb. Log., 1988)

Synthesizing Inductive Expertise - Daniel N. Osherson; Michael Stob; Scott Weinstein (Inf. Comput., 1988)

On Approximate Truth. - Daniel N. Osherson; Michael Stob; Scott Weinstein (COLT, 1989)

Paradigms of truth detection. - Daniel N. Osherson; Scott Weinstein (J. Philos. Log., 1989)

A Mechanical Method of Successful Scientific Inquiry. - Daniel N. Osherson; Michael Stob; Scott Weinstein (COLT, 1990)

Joshua Stern, Ormond Wilkie, Michael Stob, Edward E. Smith: Default Probability. - Daniel N. Osherson (Cogn. Sci., 1991)

A Universal Inductive Inference Machine. - Daniel N. Osherson; Michael Stob; Scott Weinstein (J. Symb. Log., 1991)

A Universal Method of Scientific Inquiry. - Daniel N. Osherson; Michael Stob; Scott Weinstein (Mach. Learn., 1992)

Relevant consequence and empirical inquiry. - Daniel N. Osherson; Scott Weinstein (J. Philos. Log., 1993)

Open Problems in "Systems That Learn". - Mark A. Fulk; Sanjay Jain 001; Daniel N. Osherson (J. Comput. Syst. Sci., 1994)

A note on the use of probabilities by mechanical learners. - Eric Martin 002; Daniel N. Osherson (EuroCOLT, 1995)

A Source of Bayesian Priors. - Daniel N. Osherson; Edward E. Smith; Eldar Shafir; Antoine Gualtierotti; Kevin Biolsi (Cogn. Sci., 1995)

On the danger of half-truths. - Daniel N. Osherson; Scott Weinstein (J. Philos. Log., 1995)

Formal Learning Theory. - Daniel N. Osherson; Dick de Jongh; Eric Martin 002; Scott Weinstein (Handbook of Logic and Language, 1997)

Scientific Discovery Based on Belief Revision. - Eric Martin 002; Daniel N. Osherson (J. Symb. Log., 1997)

Learning to Coordinate; a Recursion Theoretic Perspective. - Franco Montagna; Daniel N. Osherson (Synth., 1999)

Scientific Discovery on Positive Data via Belief Revision. - Eric Martin 002; Daniel N. Osherson (J. Philos. Log., 2000)

Induction by Enumeration. - Eric Martin 002; Daniel N. Osherson (Inf. Comput., 2001)

Eliminating Incoherence from Subjective Estimates of Chance. - Randy Batsell; Lyle Brenner; Daniel N. Osherson; Spyros Tsavachidis; Moshe Y. Vardi (KR, 2002)

Evidential diversity and premise probability in young children's inductive judgment. - Yafen Lo; Ashley Sides; Joseph Rozelle; Daniel N. Osherson (Cogn. Sci., 2002)

The conjunction fallacy: a misunderstanding about conjunction? - Katya Tentori; Nicolao Bonini; Daniel N. Osherson (Cogn. Sci., 2004)

Scalable Algorithms for Aggregating Disparate Forecasts of Probability. - Joel B. Predd; Sanjeev R. Kulkarni; H. Vincent Poor; Daniel N. Osherson (FUSION, 2006)

Elementary Proof of a Theorem of Jean Ville - Elliott H. Lieb; Daniel N. Osherson; Scott Weinstein (CoRR, 2006)

Aggregating disparate estimates of chance. - Daniel N. Osherson; Moshe Y. Vardi (Games Econ. Behav., 2006)

Functional neuroanatomy of deductive inference: A language-independent distributed network. - Martin M. Monti; Daniel N. Osherson; Michael J. Martinez; Lawrence M. Parsons (NeuroImage, 2007)

Aggregating Probabilistic Forecasts from Incoherent and Abstaining Experts. - Joel B. Predd; Daniel N. Osherson; Sanjeev R. Kulkarni; H. Vincent Poor (Decis. Anal., 2008)

Recognizing Strong Random Reals. - Daniel N. Osherson; Scott Weinstein (Rev. Symb. Log., 2008)

Methods for distance-based judgment aggregation. - Michael K. Miller; Daniel N. Osherson (Soc. Choice Welf., 2009)

Probabilistic coherence and proper scoring rules. - Joel B. Predd; Robert Seiringer; Elliott H. Lieb; Daniel N. Osherson; H. Vincent Poor; Sanjeev R. Kulkarni (IEEE Trans. Inf. Theory, 2009)

Improving aggregated forecasts of probability. - Guanchun Wang; Sanjeev R. Kulkarni; H. Vincent Poor; Daniel N. Osherson (CISS, 2011)

Detecting deviations from randomness. - Jiaying Zhao; Daniel N. Osherson (CogSci, 2011)

Aggregating Large Sets of Probabilistic Forecasts by Weighted Coherent Adjustment. - Guanchun Wang; Sanjeev R. Kulkarni; H. Vincent Poor; Daniel N. Osherson (Decis. Anal., 2011)

Evidence for conceptual combination in the left anterior temporal lobe. - Sean G. Baron; Daniel N. Osherson (NeuroImage, 2011)

Formal Learning Theory in Context. - Daniel N. Osherson; Scott Weinstein (Inductive Logic, 2011)

Updating: Learning versus supposing. - Jiaying Zhao; Vincenzo Crupi 001; Katya Tentori; Branden Fitelson; Daniel N. Osherson (CogSci, 2012)

Remarks on "Random Sequences" - Branden Fitelson; Daniel N. Osherson (CoRR, 2012)

Quantified preference logic - Daniel N. Osherson; Scott Weinstein (CoRR, 2012)

Notes on random reals - Daniel N. Osherson; Scott Weinstein (CoRR, 2012)

Preference based on Reasons. - Daniel N. Osherson; Scott Weinstein (Rev. Symb. Log., 2012)

Modal Logic for Preference Based on Reasons. - Daniel N. Osherson; Scott Weinstein (In Search of Elegance in the Theory and Practice of Computation, 2013)

Deontic modality based on preference. - Daniel N. Osherson; Scott Weinstein (CoRR, 2014)

Alternation blindness in the perception of binary sequences. - Ru Qi Yu; Daniel N. Osherson; Jiaying Zhao (CogSci, 2017)

Feature Ratings and Empirical Dimension-Specific Similarity Explain Distinct Aspects of Semantic Similarity Judgments. - Marius Catalin Iordan; Cameron T. Ellis; Michael Lesnick; Daniel N. Osherson; Jonathan Cohen 003 (CogSci, 2018)