Blocks world
The blocks world is a planning domain in artificial intelligence. The algorithm is similar to a set of wooden blocks of various shapes and colors sitting on a table. The goal is to build one or more vertical stacks of blocks. Only one block may be moved at a time: it may either be placed on the table or placed atop another block. Because of this, any blocks that are, at a given time, under another block cannot be moved. Moreover, some kinds of blocks cannot have other blocks stacked on top of them.[1]
The simplicity of this toy world lends itself readily to classical symbolic artificial intelligence approaches, in which the world is modeled as a set of abstract symbols which may be reasoned about.
Motivation
Artificial Intelligence can be researched in theory and with practical applications. The problem with most practical application is, that the engineers don't know how to program an AI system. Instead of rejecting the challenge at all the idea is to invent an easy to solve domain which is called a toy problem. Toy problems were invented with the aim to program an AI which can solve it. The blocks world domain is an example for a toy problem. Its major advantage over more realistic AI applications is, that many algorithms and software programs are available which can handle the situation.[2] This allows to compare different theories against each other.
In its basic form, the blocks world problem consists of cubes in the same size which have all the color black. A mechanical robot arm has to pick and place the cubes.
Theses/projects which took place in a blocks world
- Terry Winograd's SHRDLU
- Patrick Winston's Learning Structural Descriptions from Examples and Copy Demo
- Gerald Jay Sussman's Sussman anomaly
Decision problem (Gupta and Nau, 1992): Given a starting Blocks World, an ending Blocks World, and an integer L > 0, is there a way to move the blocks to change the starting position to the ending position with L or less steps?
This decision problem is
See also
References
- ^ Russell & Norvig 2003.
- .
- ^ Chenoweth, Stephen V (1991). On the NP-Hardness of Blocks World. AAAI Proceedings of the ninth national conference on Artificial Intelligence. pp. 623--628.
- .
- ^ Zilles, Sandra; Holte, Robert C (2009). Downward path preserving state space abstractions. Eighth Symposium on Abstraction, Reformulation, and Approximation.
- .
Sources
- ISBN 0-13-790395-2
External links
- Media related to Blocks worlds (artificial intelligence) at Wikimedia Commons