Probability and plurality for aggregations of learning machines

Information and Computation

Volumn 77, Issue 1, 1988, Pages 77-92

  Pitt, Leonard ^a   Smith, Carl H ^b  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 38249030604     PISSN: 08905401     EISSN: 10902651     Source Type: Journal    
DOI: 10.1016/0890-5401(88)90046-6     Document Type: Article

References (20)

1. Inductive inference: Theory and methods
2. Inductive inference
3. Two theorems on the limiting synthesis of functions
4. Toward a mathematical theory of inductive inference
5. Comparison of identification criteria for machine inductive inference
6. On the error correcting power of pluralism in BC-type inductive inference
7. Some decidability results on grammatical inference of best programs
8. Functions computable in the limit by probabilistic machines
9. Finite identification of general recursive functions by probabilistic strategies
10. On the principle capabilities of probabilistic algorithms in inductive inference
11. Language identification in the limit
12. Aggregating inductive expertise
13. A Characterization of Probabilistic Inference
14. Probabilistic synthesis of enumerated classes of functions
15. Probabilistic program synthesis
16. The power of pluralism for automatic program synthesis
17. A theory of the learnable
18. On the power of probabilistic strategies in inductive inference