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Planning with Recursive Subgoals [chapter]

Han Yu, Dan C. Marinescu, Annie S. Wu, Howard Jay Siegel
2004 Lecture Notes in Computer Science  
In this paper, we introduce an effective strategy for subgoal division and ordering based upon recursive subgoals and combine this strategy with a genetic-based planning approach.  ...  Empirical results show that the recursive subgoal strategy reduces the size of the search space and improves the quality of solutions to planning problems.  ...  (b) The goal configuration Fig. 2 . 2 The steps for solving a 4 × 4 Sliding-tile puzzle using the recursive subgoal strategy. (a) The first subgoal. (b) The second subgoal.  ... 
doi:10.1007/978-3-540-30133-2_3 fatcat:fgjtp3g375fj5emxtyw2iovqsu

Genetic-Based Planning With Recursive Subgoals

Han Yu, Dan C. Marinescu, Annie S. Wu, Howard Jay Siegel
2008 Zenodo  
In this paper, we introduce an effective strategy for subgoal division and ordering based upon recursive subgoals and combine this strategy with a genetic-based planning approach.  ...  Empirical results show that the recursive subgoal strategy reduces the size of the search space and improves the quality of solutions to planning problems.  ...  (b) The goal configuration Fig. 2 2 The steps for solving a 4 × 4 Sliding-tile puzzle using the recursive subgoal strategy. (a) The first subgoal. (b) The second subgoal.  ... 
doi:10.5281/zenodo.1080693 fatcat:jrr3eaykd5b6ffxhloeupmczpa

Chunking in Soar: The anatomy of a general learning mechanism

John E. Laird, Paul S. Rosenbloom, Allen Newell
1986 Machine Learning  
In previous work we have demonstrated how the combination of chunking and Soar could acquire search-control knowledge (strategy acquisition) and operator implementation rules in both search-based puzzle  ...  Soar is a general problem-solving architecture with a rule-based memory.  ...  Acknowledgements We would like to thank Pat Langley and Richard Korf for their comments on an earlier draft of this paper.  ... 
doi:10.1007/bf00116249 fatcat:e4degbku4rarree777liyjifqa

Page 8103 of Mathematical Reviews Vol. , Issue 98M [page]

1998 Mathematical Reviews  
8103 98m:68241 68T20 O0A69 03-04 03B35 Huang, Guoxiang |Huang, Guo Xiang’| (1-HI; Honolulu, HI); Myers, Dale (1-HI; Honolulu, HI) Subgoal strategies for solving board puzzles. (English summary) J.  ...  One of these strategies automatically generates subgoals; another finds efficient sets of rules for the subgoals. The subgoals are based on the re- versal of simple logical implications.  ... 

Problem representation for refinement

H. Altay Guvenir, Varol Akman
1992 Minds and Machines  
In this paper we attempt to develop a problem representation technique which enables the decomposition of a problem into subproblems such that their solution in sequence constitutes a strategy for solving  ...  Then, the statement representing the set of goal states can be partitioned into its subsets each of which becomes a subgoal of the resulting strategy.  ...  Banerji (Temple University) for useful conversations.  ... 
doi:10.1007/bf02454223 fatcat:ftlgye7ztbfcpcloc2ppfy3bba

SOAR: An architecture for general intelligence

John E. Laird, Allen Newell, Paul S. Rosenbloom
1987 Artificial Intelligence  
The board in the eight puzzle is represented by nine cells (the 3x3 square at the bottom of the figure), one for each of the possible locations for the tiles.  ...  This requires task-specific knowledge, so either productions must exist that evaluate the contending objects, or a subgoal will be created to perform this evaluation (see below for a default strategy for  ...  In these runs, chunking occurrcd from the bottom up, that is, chunks were built for a goal only if no subgoals occurred.  ... 
doi:10.1016/0004-3702(87)90050-6 fatcat:smvp6m2uczerlb74el3ftqk6hy

Searching with pattern databases [chapter]

Joseph C. Culberson, Jonathan Schaeffer
1996 Lecture Notes in Computer Science  
For sliding tile puzzles, the database enumerates all possible patterns containing N tiles and, for each one, contains a lower bound on the distance to correctly move all N tiles into their correct nal  ...  For the 15-Puzzle, iterative-deepening A* with pattern databases (N=8) reduces the total number of nodes searched on a standard problem set of 100 positions by over 1000-fold.  ...  Acknowledgements Our thanks to Richard Korf for making his implementation of linear con icts available to us. This work originated out of discussions with Alexander Reinefeld.  ... 
doi:10.1007/3-540-61291-2_68 fatcat:4delkoybvreabha2usl4eknueq

Locus of Difficulty in Multistage Mathematics Problems

Paul Ayres, John Sweller
1990 American Journal of Psychology  
-1 was rejected at the subgoal-2 stage in preference for a backward working means-ends strategy.  ...  Ernst and Newell gave GPS eleven different tasks to solve, three of which were the above-mentioned puzzle problems. GPS successfully solved the three problems but with varying efficiency.  ... 
doi:10.2307/1423141 fatcat:tojxevxusvfbpcshcihg5f7bve

Cognitive Load During Problem Solving: Effects on Learning

John Sweller
1988 Cognitive Science  
These mechanisms have implications for learning, as well as problem solving.  ...  Problem-solving skill is highly valued.  ...  Evidence of Interference Between Conventional Problem Solving and Schema Acquisition The initial findings were obtained using puzzle problems.  ... 
doi:10.1207/s15516709cog1202_4 fatcat:twg4z6fhhvbbvclsrzyypirra4

Cognitive load during problem solving: Effects on learning

J Sweller
1988 Cognitive Science  
These mechanisms have implications for learning, as well as problem solving.  ...  Problem-solving skill is highly valued.  ...  Evidence of Interference Between Conventional Problem Solving and Schema Acquisition The initial findings were obtained using puzzle problems.  ... 
doi:10.1016/0364-0213(88)90023-7 fatcat:kptjmqennfag7oo574fjzfxwam

Deriving Concepts and Strategies from Chess Tablebases [chapter]

Matej Guid, Martin Možina, Aleksander Sadikov, Ivan Bratko
2010 Lecture Notes in Computer Science  
Complete tablebases, indicating best moves for every position, exist for chess endgames.  ...  There is no doubt that tablebases contain a wealth of knowledge, however, mining for this knowledge, manually or automatically, proved as extremely difficult.  ...  This method extracts a strategy for solving problems that require search (like chess, checkers etc.).  ... 
doi:10.1007/978-3-642-12993-3_18 fatcat:jxfuyowiorgubfmhe35oxeayxq

Problem-Solving Restructuration: Elimination of Implicit Constraints

Jean-François Richard, Sébastien Poitrenaud, Charles Tijus
1993 Cognitive Science  
This has been done, for instance, in the modeling of problem-solving situations for avariety of river-crossing problems (Schmalhofer & Polson, 1986) and the simulation of the action side of rules when  ...  solving the Tower of Hanoi problem (Karat, 1982) .  ...  We would like to thank three anonymous reviewers for helpful comments on an earlier version of the article.  ... 
doi:10.1207/s15516709cog1704_2 fatcat:ya7ha6f4gzbx7okw6vour3oxhm

Problem-solving restructuration: Elimination of implicit constraints

J Richard
1993 Cognitive Science  
This has been done, for instance, in the modeling of problem-solving situations for avariety of river-crossing problems (Schmalhofer & Polson, 1986) and the simulation of the action side of rules when  ...  solving the Tower of Hanoi problem (Karat, 1982) .  ...  We would like to thank three anonymous reviewers for helpful comments on an earlier version of the article.  ... 
doi:10.1016/0364-0213(93)90002-p fatcat:dnvxikaoyvcotm76ekototomee

The effect of conscious controlled verbalization cognitive strategy on transfer in problem solving

Mary E. Ahlum-Heath, Francis J. Di Vesta
1986 Memory & Cognition  
The effect of controlled verbalization on learning to solve complex problems was investigated.  ...  One factor was the presence or absence of a practice series which required participants to provide verbal rationales for their moves.  ...  Although means-ends strategies were examined in the present study, it should be recognized that the Tower of Hanoi puzzle can be solved by goal reduction (or rule induction).  ... 
doi:10.3758/bf03197704 pmid:3736402 fatcat:yt3u3vi37ncphfomrufgbc7dwe

Varieties of Learning in Soar: 1987 [chapter]

David M. Steier, John E. Laird, Allen Newell, Paul S. Rosenbloom, Rex A. Flynn, Andrew Golding, Thad A. Polk, Olin G. Shivers, Amy Unruh, Gregg R. Yost
1987 Proceedings of the Fourth International Workshop on MACHINE LEARNING  
When Soar finishes working on a subgoal, it can learn from its experience by building productions called chunks for use in future problem solving.  ...  Effects of chunking in different tasks Puzzles and toy problems: The first demonstrations of the power of chunking as a learning mechanism were obtained with tasks such as solving the eight-puzzle and  ... 
doi:10.1016/b978-0-934613-41-5.50034-9 fatcat:5ytxdt7zhfhh5l6ziegqlbftem
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