This paper reports the results of a two-part data analysis of learning in a repeated costly decision experiment. In the ยฎrst part we test payo dominance under the hypothesis of expected payo maximization. We utilize a dynamic probability distribution over decisions for each player, characterizing wh
Inclusion Problems in Parallel Learning and Games
โ Scribed by Martin Kummer; Frank Stephan
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 840 KB
- Volume
- 52
- Category
- Article
- ISSN
- 0022-0000
No coin nor oath required. For personal study only.
โฆ Synopsis
In a recent paper Kinber, Smith, Velauthapillai, and Wiehagen introduced a new notion of parallel learning.'' They call a set S of functions (m, n)-learnable if there is a learning machine which for any n-tuple of pairwise distinct functions from S learns at least m functions correctly from examples of their behavior after seeing some finite amount of input. One of the basic open questions in this area is the inclusion problem,'' i.e., the question for which m, n, h, k, every (m, n)-learnable class is also (h, k)-learnable. In this paper we develop a general approach to solve this problem. The idea is to associate with each m, n, h, k in a uniform way a finite 2-player game such that the first player has a winning strategy in this game iff every (m, n)-learnable class is (h, k)-learnable. In this way we take the recursion theoretic disguise off the problem and isolate its combinatorial core. We also explicitly characterize the ``strength'' of each particular noninclusion by the complexity of an oracle which is needed to overcome it. It turns out that there are exactly three different types of noninclusions.
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