📓 content/R- Constraint relaxation and chunk decomposition in insight problem solving.md by @scalingsynthesis ☆

#[[references]]
- Title: Constraint relaxation and chunk decomposition in insight problem solving
- Meta:
  - Authored by:: [[G. Knoblich]] [[S. Ohlsson]] [[H. Haider]] [[D. Rhenius]]
  - Year: [[1999]]
  - Publication: Journal of Experimental Psychology: Learning, Memory, and Cognition
  - URL: Knoblich et al. (1999). Constraint relaxation and chunk decomposition in insight problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition
- Content
  - Abstract
    - Insight problem solving is characterized by impasses, states of mind in which the thinker does not know what to do next. ==The authors hypothesized that impasses are broken by changing the problem representation, and 2 hypothetical mechanisms for representational change are described: the relaxation of constraints on the solution and the decomposition of perceptual chunks. These 2 mechanisms generate specific predictions about the relative difficulty of individual problems and about differential transfer effects.== The predictions were tested in 4 experiments using matchstick arithmetic problems. The results were consistent with the predictions. Representational change is a more powerful explanation for insight than alternative hypotheses, if the hypothesized change processes are specified in detail. Overcoming impasses in insight is a special case of the general need to override the imperatives of past experience in the face of novel conditions.
#references
- Title: Constraint relaxation and chunk decomposition in insight problem solving
- Meta
  - Tags: [[D/Solution-Diversity]] [[D/Synthesis Infrastructure]] [[D/Computational Analogy]]
  - Authored by:: [[Gunther Knoblich]] , [[Stellan Ohlsson]] , H. Haider , D. Rhenius
  - Year: [[1999]]
  - Publication: [[Journal of Experimental Psychology: Learning, Memory, and Cognition]]
- #lit-context
  - [[Stellan Ohlsson]] is prominent authority on [[Insight problem solving]]
  - Design: have people do two blocks: in second block people got a lot btter, so probably best to consider block 1 to really feel out the ffects of problem types
    - Vary problem difficulty by varying constraint hardness and chunk tightness, both together and independently
- #[[📝 lit-notes]]
  - Two key mechanisms proposed for overcoming [[Impasses]] (aka [[fixation]], which is diagnosed as a suboptimal [[problem formulation]]): 1) [[constraint relaxation]], and [[chunk decomposition]]
    - If constraints are not considered explicitly, possible to over/under-constrain problem representation (through implicit reminding) (p. 1535)
      - Citations here…
      - ⥅ [[https://firebasestorage.googleapis.com/v0/b/firescript-577a2.appspot.com/o/imgs%2Fapp%2Fmegacoglab%2Fe7MM5TgRHu.png?alt=media&token=b6422974-6fd1-4cae-b8b8-bbc0a44477fa]]
      - Therefore, if problem solver is able to relax unnecessary constraints, they can find a problem representation that admits solution, and overcome the impasse
    - Argument for [[chunk decomposition]] as a mechanism of breaking [[fixation]] and [[Impasses]]
      - People create chunks to organize experience.
      - Encountering a novel problem activates some chunks from past experiences. Not all of them will be helpful; and some will be actively unhelpful. And some will need to be decomposed ([[compression]] reversed??)
      - Decomposing is harder for "tighter" chunks: where the components are not (obviously) meaningful units on their own
      - Thus, problems with tight chunks are harder to solve.
    - Evidence for this: when they made it harder to decompose chunks (even with identical constraint types), people were about half as likely to solve the problem (p. 1540).
    - What are chunks??
      - "chunks" for Knoblich are not similar to [[Design Patterns]] or [[Frames]] - they are more like visual features, that exist at multiple levels of hierarachies. (cf.
      - Knoblich characterizes [[Chunk]]s as #patterns that capture recurring constellations of features or components" (p. 1535)
        
        ⥅ [[https://firebasestorage.googleapis.com/v0/b/firescript-577a2.appspot.com/o/imgs%2Fapp%2Fmegacoglab%2F_jL1XWtx0l.png?alt=media&token=85dd6f16-4814-40d4-975f-114c303aaddc]]
      - To [[@chaseMindEyeChess1973]] on the idea of [[Chunking]] as a mechanism for expert performance #expertise
        
        Which itself goes back fruther to [[de Groot]], back in the mid-1960’s
        
        Be careful, though! Their idea of [[Chunking]] is closer to the idea of [[compression]] - packing a huge amount of information into a smaller unit, abstracting away a lot of things.
  - Observed some transfer effects across blocks: once you see a constraint relaxed or decompose a chunk, a later problem that .
    - Somewhat anecdotal in Experiment 1, and directly validated in Experiment 2