Titlebook: Change of Representation and Inductive Bias; D. Paul Benjamin Book 1990 Kluwer Academic Publishers 1990 autonomous system.hierarchical pla

Subdue

Planning disassembly with stochastic yields,g as output. One language bias is stronger (weaker) than another if the hypothesis space of the first bias is a subset (superset) of the hypothesis space of the second bias. For example, a system that always produces a conjunctive hypothesis has a stronger language bias than a system that can produce arbitrary disjunctions of conjunctions.

murmur

The Springer International Series in Engineering and Computer Sciencehttp://image.papertrans.cn/c/image/223727.jpg

dictator

Decompiling Problem-Solving Experience to Elucidate Representational Distinctions,es efficiency, but flexibility is greatly compromised. In this paper I discuss an alternative that extracts relevant distinctions from problem-solving traces and creates explicit representational terms for them. The new terms are seamlessly integrated into declarative knowledge and are effectively utilized in subsequent problem solving.

IRATE

Knowledge as Bias, generalize training data before doing empirical learning. The combination operates like empirical learning given no knowledge, but can utilize knowledge when provided, and therefore exhibits behavior along aspectrum from knowledge-poor to knowledge-rich learning. When used in this way knowledge can be viewed as an explicit bias for learning.

VICT

Hemodialysis

流逝

finite

HAIL

Celiac-Plexus

https://doi.org/10.1007/978-0-387-48576-8ot well understood. This paper formally defines hierarchical planning, shows that the technique can reduce an exponential search space to a linear one, and identifies the assumptions under which this analysis holds. Since these assumptions would be difficult to guarantee in general, the paper identi